When analyzing user geospatial information through deep learning methods, it is typically necessary to annotate existing geospatial data. Currently, manual annotation methods are commonly employed, suffering from issues related to low efficiency and accuracy. This design is based on the TensorFlow deep learning framework and first realizes the BiLSTM+CRF+AGG deep learning model. Among the models, AGG is the aggregation layer, which is introduced to solve the problem of solid particle size equilibrium. Secondly, based on the characteristics of original data and professional data, an automatic labeling algorithm is proposed. The algorithm first preprocesses the acquired original data set and professional data set, The most valuable unlabeled data set which can make the training model converge quickly is selected from the original data set as the target data set. Sort the target data set based on preset rules and set annotation parameters for the sorted target data set. Based on the set annotation parameters, the corpus is synthesized and used as the annotation result. Thirdly, based on the active learning strategy, a manual annotation auxiliary scheme is proposed, and an Excel generation module that is convenient for manual annotation correction is designed and developed to further improve the efficiency and quality of annotation through iterative processing. The combination of the BiLSTM+CRF+AGG deep learning model and high-quality annotation can accurately identify non-standard, incomplete, or even incorrect geographical information entities. This annotation method has found successful practical application within the context of the research project and has been granted an invention patent.

The integration of metal nanoparticles and solid carriers can achieve ideal stability, high load and good conductivity. In this work, copper nanoparticles (Cu NPs) were sequentially deposited on a cobalt metal-organic framework (Co-MOF) by bonding with exposed imino groups, followed by a reduction reaction to prepare a new Cu@Co-MOF composite. Cu@Co-MOF acts as a non-enzymatic electrochemical sensor to detect glucose (Glu) in an alkaline medium. The composite working electrode of Cu@Co-MOF/GCE (GCE = glassy carbon electrode) improves the electrocatalytic activity for Glu oxidation. Cu@Co-MOF/GCE shows excellent electrocatalytic performances in Glu concentration ranging 0.005~1.8 mmol∙L⁻¹ (mM): the sensitivities are 282.89 μA∙mM⁻¹∙cm⁻² in 0.005-0.4 mM Glu and 113.15 μA∙mM⁻¹∙cm⁻² in 0.4-1.8 mM Glu respectively with low detection limit of 1.6 μM (S/N = 3) and high selectivity and stability.

(1) Background: Previous systematic review suggested a beneficial effect of progressive muscle relaxation (PMR) for cancer patients receiving chemotherapy. However, poor quality of eligible studies impaired the reliability and validity of findings. Moreover, additional potential studies with good quality published in Chinese language have been published recently. The aim of the present systematic review was to investigate the value of PMR training in preventing and alleviating nausea and vomiting caused by chemotherapy among cancer patients. (2) Methods: We assigned two independent investigators to search all potential studies in PubMed, Cochrane Controlled Register of Trial (CENTRAL), Cumulative Index to Nursing and Allied Health Literature (CINAHL), China Biomedical Literature database (CBM), China National Knowledge Infrastructure (CNKI), and Wanfang data. We used data extraction sheet extracted all essential information, and used the Cochrane risk of bias assessment tool to appraise the quality of eligible studies. Finally, we qualitatively summarized the results of all included studies. (3) Results: Six studies enrolling 288 patients were considered to meet our selection criteria finally. Of these 6 studies, three were labeled as moderate quality, and the remaining studies were low quality. All included studies consistently suggested that PMR has a positive impact on nausea and vomiting caused by chemotherapy among cancer patients especially alleviating the incidence, frequency and degree of delayed nausea and vomiting. (4) Conclusions: Independent studies indicated that PMR was a beneficial approach to prevent and alleviate nausea and vomiting caused by chemotherapy among cancer patients. However, further studies considering other types of primary tumors should be designed in order to increase the generality of PMR because studies included in the present systematic review mainly enrolled lung cancer and breast cancer.

Address parsing is a crucial task in natural language processing, particularly for Chinese addresses. The complex structure and semantic features of Chinese addresses present challenges due to their inherent ambiguity. Additionally, different task scenarios require varying levels of granularity in address components, further complicating the parsing process. To address these challenges and adapt to low-resource environments, we propose CapICL, a novel Chinese address parsing model based on the In-Context Learning (ICL) framework. CapICL leverages a sequence generator, regular expression matching, BERT semantic similarity computation, and GPT modeling to enhance parsing accuracy by incorporating contextual information. We construct the sequence generator using a small annotated dataset, capturing distribution patterns and boundary features of address types to model address structure and semantics, mitigating interference from unnecessary variations. We introduce the REB-KNN algorithm, which selects similar samples for ICL-based parsing using regular expression matching and BERT semantic similarity computation. The selected samples, raw text, and explanatory text are combined to form prompts, and inputted into the GPT model for prediction and address parsing. Experimental results demonstrate significant achievements of CapICL in low-resource environments, reducing dependency on annotated data and computational resources. Our model's effectiveness, adaptability, and broad application potential are validated, showcasing its positive impact in natural language processing and geographical information systems.

In order to realize the sustainable utilization of water resources and the sustainable development of economy, the evaluation index system of water use efficiency system and economic development system was constructed. Entropy weight method and comprehensive evaluation method were adopted to determine the index weights and conduct comprehensive evaluation for the two systems. The coupling coordination model was used to calculate the coupling degree, coordination degree and coupling coordination degree of the two systems. The annual coupling stage and coupling coordination intensity of the two systems were analyzed and determined. The results showed that the comprehensive evaluation values of both water use efficiency system and economic development system in Jinan City increased greatly from 2008 to 2017, and showed a changing trend of ups and downs. The two systems were in the antagonistic stage, and were gradually approaching the running-in stage, indicating that they were in the state of common development. The coupling coordination degree of the two systems gradually increased in waves, progressed from the moderately to the highly coordinated coupling. In the future, if the water control path appropriate to Jinan City can be explored actively, the water-saving kinetic energy of economic development can be increased constantly, and the linkage effect between economic development and water resources utilization can be given full play to, the two systems will be in the orbit with the benign interaction and healthy harmonious development.

Our aim was to evaluate efficacy and safety of 30mL CaO alone or plus Asc in bowel preparation before colonoscopy. Two hundred and forty six patients were allocated randomly to ingest 2L PEG with 30mL CaO, 1L PEG with 30mL CaO plus 5g Asc, or 3L PEG. We used Boston Bowel Preparation Scale (BBPS) to evaluate bowel preparation efficacy. We also determined other outcomes such as procedure time, polyp or adenoma detection rate and adverse events (AEs). Of 282 patients recruited, 36 were excluded. Groups were matched for baseline characteristics except weight (P = 0.020) and body mass index (BMI) (P = 0.003). Patient’s satisfaction were higher in 2L PEG-CaO (P = 0.016) and 1L PEG-CaO-Asc groups (P = 0·017). Patients’ compliance was 67.5%, 71.4% and 80.5% in 3L PEG, 2L PEG-CaO and 1L PEG-CaO-Asc groups (P = 0.014). Adequate bowel preparation rate was 75%, 78.57% and 53.66% in 3L PEG, 2L PEG-CaO and 1L PEG-CaO-Asc groups (P = 0.021). There were no differences in terms of remaining outcomes. Despite an increase in patients’ satisfaction and compliance, 1L PEG-CaO-Asc significantly decreased adequate bowel preparation rate. However, 2L PEG-CaO improved the patients' satisfaction and compliance and increased adequate bowel preparation rate.

The chitin synthase B gene is a key enzyme in the chitin synthesis of insect peritrophic matrix (PM), affecting insects' feeding behavior. The chitin synthase B gene has been cloned from the transcription library of Heortia vitessoides Moore. RT-qPCR showed that HvChsb was highly expressed in the larval stage of H. vitessoides, especially on the first day of the prepupal stage, and in the midgut of larvae and the abdomen of adults. After starvation treatment, HvChsb was found to be significantly inhibited with time. After 48 h of starvation, the feeding experiment showed that HvChsb increased with the prolongation of the refeeding time. The experimental data showed that feeding affected the expression of HvChsb. HvChsb was effectively silenced by RNA interference, so its function was lost, significantly decreasing the survival rate of H. vitessoides. The survival rate from larval-to-pupal stages was only 43.33%, accompanied by abnormal phenotypes. It can be seen that HvChsb plays a key role in the average growth and development of H. vitessoides.

This paper aims to quantify the influence of hydrogen embrittlement on Wierzbicki and Xue (W-X) model parameters. This model has 4 parameters which have been obtained by tensile tests on smooth specimens, tensile notch specimens, single notch tensile specimens (SENT) and pure shear specimens. Hydrogen embrittlement has been obtained by electrolytic method. Application of the (W-X) model has been done to get the local resistance used to predict failure by the Volumetric Method (VM). An example is given for the case of an embedded pipe submitted to service pressure and lateral seismic displacement. The effect of this displacement is then assimilated to the shearing of the straight section of the pipe. The pipe shows a corrosion defect considered a semi-elliptical crack. The influence of hydrogen embrittlement on local strain resistance and safety factors is discussed.

Senescence-accelerated mouse prone 8 (SAMP8) mice exhibit cognitive defects and neuron loss with aging, and are used to study anti-aging effects of Dendrobium nobile alkaloids (DNLA). SAMP8 mice were orally given DNLA from ages 6 to 10 months. At 10 months of age, behavioral tests and neuron damage were evaluated. Protein was extracted and subjected to phosphorylated proteomic analysis. The cognitive deficits and neuron loss in hippocampus and cortex of aged SAMP8 mice were improved by DNLA. Hippocampal proteomic analysis showed differentially expressed protein/genes in SAMP8 compared to age-matched senescence-accelerated resistant mice, including altered tubulin binding, microtubule binding, etc. via Gene Oncology. KEGG revealed endocytosis, mRNA surveillance, tight junction, protein processing in endoplasmic reticulum, aldosterone synthesis and secretion, and glucagon signaling pathway changes. Upregulated protein/genes in the hippocampus of SAMP8 mice, such as Lmtk3, Usp10, Dzip1, Csnk2b, and Rtn1, were attenuated by DNLA; whereas downregulated protein/genes, such as Kctd16, Psd3, Bsn, Atxn2l, and Kif1a, were rescued by DNLA. The aberrant protein/gene expressions of SAMP8 mice were correlated with transcriptome changes of Alzheimer’s disease in the GEO database, and were attenuated by DNLA. Thus, DNLA improved cognitive dysfunction and ameliorated neuronal injury in aged SAMP8 mice, and attenuated aberrant protein/gene expressions.

In order to understand the defense response of Sanchezia nobilis to biotic and abiotic stresses, this study investigated the phenomenon of S. nobilis under biotic of feeding by Achatina fulica, and measured the temporal changes of malondialdehyde content, catalase and peroxidase activities under biotic of feeding by Achatina fulica and abiotic stress of garden pruning conditions on S. nobilis. The results showed that: 1) S. nobilis was seriously damaged by A. fulica and the average hourly food intake of A. fulica is 0.22 ± 0.01 g. 2) Leaf cutting stimulation and snail feeding stress significantly affected the content of malondialdehyde, the activities of catalase and peroxidase in the leaves of S. nobilis. 3) Compared with the control group, the snail feeding and leaf cutting stimulated stress could induce the leaf of S. nobilis to synthesize more malondialdehyde under varying durations, and the activities of catalase and peroxidase were significantly enhanced in a short time, and the induction response of snail feeding biological stress was faster than that of leaf cutting stimulated abiotic stress. 4) After the defense enzyme was strengthened, the activities of catalase and peroxidase in the feeding stress group of snails showed a gradual downward trend, while the activities of catalase and peroxidase in the leaf cutting stimulation stress group showed a first upward and then downward trend, indicating that abiotic stress had more lasting effects on plants than biological stress. It can be seen that biotic stress and abiotic stress significantly affect the defense response of plants, and the defense-related substances malondialdehyde, catalase and peroxidase play an important role in plants' response to biotic and abiotic stress. This study has important production guidance significance for carrying out stress resistance breeding or cultivation management of garden plants.

The aspirated hypersonic air-breathing propulsion system requires a large amount of power generation, but its special structure makes it impossible to adopt common power generation methods. The high-temperature gaseous hydrocarbon fuel thermal power generation (TPG) system was developed to solve the power generation problem for hypersonic air-breathing propulsion system. But off-design operating conditions of the hypersonic propulsion system results in a more complex process for both propulsion system and the TPG system. To better analyzing the dynamic thermos-physical characteristics of hypersonic airbreathing propulsion system considering thermal-mechanical coupling process among cooling/TPG system, a dynamic analytical model was developed, and the dynamic thermos-physical characteristics of TPG system under different off-design working conditions were conducted. It can be concluded from the analytical results that the dynamic process of thermos-physical characteristics shows a complex trend under the flight Mach number and fuel equivalence ratio off-design working conditions. Such complexity of dynamic characteristics brings difficulties in fuel supply for the propulsion system.

Patients with schizophrenia had higher mortality risks and the role of antipsychotic medications remained inconclusive. In an aging society, elderly schizophrenia patients warrant increased attention. In this study, we aimed to explore medication dosage associations with mortality in schizophrenia patients, using Taiwan's national healthcare database from 2010 to 2014, with 102,964 patients with schizophrenia, and a subgroup of 6,433 elderly patients, compared to an age- and gender-matched control group. The findings revealed that schizophrenia patients with no antipsychotic exposure had the highest mortality risk as compared to the control sample—with a 3.61 and 3.37-fold risk for overall and cardiovascular mortality respectively in age and gender-adjusted model, followed by high, low, and moderate exposure groups. A similar pattern was observed in elderly schizophrenia patients but high exposure to antipsychotics was associated with the highest risk in both overall and cardiovascular mortality in elderly patients, with a 3.01, and 2.95-fold risk), respectively. In conclusion, the use of antipsychotics is beneficial to patients with schizophrenia, with recommended exposure levels being low to moderate. In elderly patients, high antipsychotic exposure was associated with the highest mortality risk. We should pay more attention to antipsychotic dosage in elderly schizophrenia patients.

End-to-end learned image compression codecs have notably emerged in recent years. These codecs have demonstrated superiority over conventional methods, showcasing remarkable flexibility and adaptability across diverse data domains while supporting new distortion losses. Despite challenges such as computational complexity, learned image compression methods inherently align with learning-based data processing and analytic pipelines due to their well-suited internal representations. The concept of Video Coding for Machines has garnered significant attention from both academic researchers and industry practitioners. This concept reflects the growing need to integrate data compression with computer vision applications. In light of these developments, we present a comprehensive survey and review of lossy image compression methods. Additionally, we provide a concise overview of two prominent international standards, MPEG Video Coding for Machines and JPEG AI. These standards are designed to bridge the gap between data compression and computer vision, catering to practical industry use cases.

This study aims to determine the protective effects of red seaweed Eucheuma cottonii (EC) ethanol extract on acute colitis disease in mice. Male BALB/c mice used for acute colitis disease model by induced 2.5% (w/v) of dextran sulfate sodium (DSS) for 7 days for all groups, except control group. The DSS-induced mice then treated by three different doses of EC extracts (0.35, 0.70, 1.75 g/kg body weight), curcumin (as a positive control, 0.10 g/kg), and a group was orally only by water. In 8^th day, the mice sacrificed and collected the blood, then measured the body weight, colon weight, and colon length. Disease activity index (DAI), pro-inflammatory such as tumor necrosis factor (TNF)-α, interleukin (IL)-1β, and IL-6, as well as IL-10 as anti-inflammatory were measured. The results showed that after treatment for 7 days, EC extract protected the weight loss and decreased the colon weight per length ratio. In addition, EC extract also decreased the pro-inflammatory cytokines expression in serum and increased the IL-10. Moreover, EC extract protected the colonic tissue damage. According to this results, the EC ethanol extract might be can used for the treatment of colitis disease.

The molecular clusters ((HO)3Si-O-Si(OH)3, and (HO)3Al-O-Si(OH)3 ) representative of aluminosilicate mineral surface were employed to study the dissolution of aluminosilicate in acidic condition via density functional theory with the M06-2X+G(d,p) methodology. The surface termination sites (Si and Al) were both tetra-coordinated and the terminal oxygen was protonated in acidic condition. In the dissolution reaction, the calculated barrier height of the six-membered ring transition state complex containing two water molecules was predicted to be lower than that of four-membered ring transition state complex containing one water molecule. In addition, the calculated barrier heights for Al-terminated sites were predicted to be lower than those for the Si-terminated sites, suggesting that breaking the Al-O bond is easier than Si-O bond in the aluminosilicate mineral surface; the barrier heights of the surface termination sites with protonated terminal oxygen were lower than those without protonated terminal oxygen. With the fracture of Si-O and Al-O bonds, the Si and Al release from the aluminosilicate. These results confirm the experimental conclusions that the acidic condition facilitates the release of Si and Al from the aluminosilicate, and the concentration of Al leaching from aluminosilicate is higher than Si.

One of the most leading causes of death worldwide is Colorectal cancer(CRC). Polyp segmentation is the most important detected measure for preventing CRC. However, there is still a missing rate for diminutive polyps and multiple ones. In order to solve the phenomenon, we propose to introduce auxiliary attention module(AAM) that can enhance the learning of features related to multiple and diminutive polyps by focusing more on the located and detailed information. Meanwhile, we design to decrease missed rate of multiple and diminutive polyps by implementing an area adaptive loss(AAL) which adapts the weight according to the area and the number of polyps. Our proposed novel AAM and AAL concentrates on training with hard examples and localized information. To evaluate the effectiveness and generalization ability of our proposed model, We utilize three different datasets of variable sizes and a cross dataset. Our proposed method achieves the best results on the Kvasir-SEG dataset, the CVC-ClinicDB dataset and the cross dataset, particularly for the Kvasir-Sessile dataset consisting of small,flat and diminutive polyps. Extensive experimental results show that our proposed DoubleAANet surpass the performance of all existing state-of-the-art segmentation methods.

This article examines the integration of artificial intelligence (AI) and robotic process automation (RPA) in financial accounting and management, underscoring their role in driving the digital transformation of corporate finance. It discusses the shortcomings of traditional financial processes and highlights the potential of AI and RPA technologies to enhance efficiency, accuracy, and cost-effectiveness. The paper also explores the limitations of RPA, such as its challenges in processing unstructured data and handling complex decision-making scenarios. Looking forward, it considers the future trends in AI and RPA, emphasizing the benefits of cloud technology in scaling automated systems and addressing associated challenges.

A Systemic Lupus Erythematosus (SLE) is a prototypical systemic autoimmune disease characterized by a complex interplay of genetic, molecular, and cellular factors. It is considered a multifactorial disorder influenced by genetic susceptibility, environmental triggers, and dysregulated immune responses. Understanding the molecular and cellular mechanisms driving SLE pathogenesis has been instrumental in developing targeted therapies to manage the disease and improve patient outcomes. In this essay, we will delve into the intricate molecular and cellular processes underlying SLE and examine the key lessons learned from human therapies.

In this study, we present a federated learning approach that combines a multi-branch network and the Oort client selection algorithm to improve the performance of federated learning systems. This method successfully addresses the significant issue of non-iid data, a challenge not adequately tackled by the commonly used MFedAvg method. Additionally, one of the key innovations of this research is the introduction of uniformity, a metric that quantifies the disparity in training time amongst participants in a federated learning setup. This novel concept not only aids in identifying stragglers but also provides valuable insights into assessing the fairness and efficiency of the system. Experimental results underscore the merits of the integrated multi-branch network with the Oort client selection algorithm and highlight the crucial role of uniformity in designing and evaluating federated learning systems.

Two interesting compounds such as quaternary ammonium lignin(QAL) and 2-ethylhexyl phosphoric acid mono-2-ethylhexyl ester (P507) were synthesized as ionic liquids(QP-ILs) for the extraction of metal ions. The extraction behavior of Co(II) and Ni(II) from chloride solution was compared between QP-ILs and P507. The results showed that the extraction rates of Co(II) and Ni(II) in the two solutions varied with the extraction conditions, but QP-ILs has stronger extractability for cobalt than P507, while Ni is on the contrary. Under the same conditions, the Co/Ni separation performance(βCo/Ni) in QP-ILs is superior to that in p507. At pH4.0, 55℃, concentration of 20%, extraction time of 10 minutes, the βCo/Ni of QP-ILs reached to 2703, while that of P507 was only 164. In conclusion, QP-ILs was more efficient than P507 for separating Co from mixed solutions.

Rapid and accurate detection of road cracks is of great significance for road health monitoring, but currently this work is mainly completed through manual site surveys. Low-altitude UAV remote sensing can obtain images with centimeter or even subcentimeter ground resolution, which provides a new efficient and economical approach for rapid crack detection. Nevertheless, crack detection networks face challenges such as edge blurring and misidentification due to the heterogeneity of road cracks and the complexity of the background. To address these issues, we propose a real-time edge reconstruction crack detection network (ERNet) which adopts multi-level information aggregation to reconstruct crack edges and improve the accuracy of segmentation between the target and background. To capture global dependencies across spatial and channel levels, we propose an efficient bilateral decomposed convolutional attention module (BDAM) that combines depth separable convolution and dilated convolution to capture global dependencies across spatial and channel levels. To enhance the accuracy of crack detection, we use a coordinate-based fusion module that integrates spatial, semantic, and edge reconstruction information. In addition, we propose an automatic measurement of crack information for extracting the crack trunk and its corresponding length and width. Experimental results demonstrate that our network achieves the best balance between accuracy and inference speed.

The mangrove plant Acanthus ilicifolius and its relative, A. mollis, have been previously proved to possess diverse pharmacological effects. Therefore, evaluating the differentially expressed proteins of these species under tidal flooding stress is essential to fully exploit and benefit from their medicinal values. The roots of A. ilicifolius and A. mollis were exposed to 6 h of flooding stress per day for 10 days. The dry weight, hydrogen peroxide (H2O2) content, anatomical characteristics, carbon and energy levels, and two-dimensional electrophoresis coupled with MALDI-TOF/TOF MS technology were used to reveal the divergent flooding resistant strategies. A. ilicifolius performed better under tidal flooding stress, which was reflected in the integrity of the morphological structure, more efficient use of carbon and energy, and a higher percentage of up-regulated proteins associated with carbon and energy metabolism. A. mollis could not survive in flooding conditions for a long time, as revealed by incomplete cell structures of the roots, less efficient use of carbon and energy, and a higher percentage of down-regulated proteins associated with carbon and energy metabolism. Energy provision and flux balance played a role in the flooding tolerance of A. ilicifolius and A. mollis.

Porcine circovirus type 2 (PCV2) is a small non-enveloped DNA virus that causes swine immunosuppression by inducing apoptosis in lymphocytes. The ORF3 protein plays a major role in PCV2-induced apoptosis in porcine kidney cells, but there is little information regarding this protein in PCV2-infected lymphocytes. In this study, hybridoma screening and epitope mapping were determined by using an indirect ELISA. The mAb 7D3 against ORF3 peptide (residues 35–65) of PCV2 were generated in this study. In vivo situation, the mAb 7D3 recognized ORF3 protein existed in PCV2-infected apoptotic porcine PBMCs. It is noteworthy that thimerosal interfered with the binding of mAb 7D3 to epitope and it was diminished by adding cysteine. Additionally, thimerosal interacting with cysteine-containing peptide was demonstrated by the PTI assay. Furthermore, thimerosal specifically interacted with the antigen-binding sites of mAb 7D3. This study suggested that thimerosal blockade the occlusion of the antigen-binding sites of mAb 7D3 to bind ORF3 peptide (residues 35–65) via thimerosal interacting with cysteine residues which should be located within the antigen-binding sites of mAb 7D3. Overall, the mAb 7D3 has been characterized and it will be a valuables tool in future studies of ORF3 function and the wider mechanism of cell apoptosis caused by PCV2 infection. Similarly, these techniques will be useful for applications in detecting thimerosal too.

The creep behaviors of TA2 and R60702 at low and intermediate temperature were presented and discussed in this paper. Experimental results indicated that an apparent threshold stress exhibited in the creep deformation of R60702. Meanwhile, the primary creep phase was found as the main pattern in the room temperature creep behavior of TA2. Compared with exponential law, the power law has been proved to be a proper constitutive model in the description of primary creep phase. It also showed that θ projection method had its significant advantage in the evaluation of accelerated creep stage. Thus, a composite model which combined power law with θ projection method was applied in the creep curves evaluation at low and intermediate temperature. Based on the multiaxial creep deformation results, the model was modified and discussed. A linear relationship existed between composite model parameters and applied load. Finally, the creep life could be accurately predicted and the composite model method is suitable for application in low and intermediate temperature creep life analysis.

The threat of fine particulate matter concentration (PM2.5) is increasing globally, Tackling this issue requires an accurate understanding of its trends and drivers. The article investigates the PM2.5 characteristics of 285 prefecture-level cities in China from 2000-2018 based on multiscale geographically weighted regression(MGWR), and the results show that（1）previous studies based on classical MGWR models may be somewhat unstable, while MGWR can reflect the scale of influence of different variables on the dependent variable, and its regression results are more reliable.（2）PM2.5 is very sensitive to carbon emission(CE) factors, and there is a high degree of spatial heterogeneity, and the influence scale of location is the smallest among all variables, close to the municipal scale.（3）In 2000, the constant term all, IS, OFT, CE, and LT positively affect PM2.5, while GDP (jurisdiction) and UR negatively affect PM2.5; in 2010, the constant term all, GDP (jurisdiction), IS, OFT and LT positively affect PM2.5, while UR and CE negatively affect PM2.5; in 2018 the constant term all, IS, OFT and CE factors positively affect PM2.5, and GDP (jurisdiction), UR and LT negatively affect PM2.5.

Autonomous vehicles (AVs) may not only reduce parking demand, but also free up on-street parking spaces. From the perspective of bus priority, converting on-street parking lots into dedicated bus lanes can both ensure bus priority and accommodate non-bus traffic, helping to reduce congestion and pollution. In order to study the impact of conversion of on-street parking lots to bus lanes on traffic flow, a microscopic simulation framework based on VISSIM is proposed in this paper. Data was collected using the floating car method and video recording method to quantify the factors affecting traffic flow due to the conversion of on-street parking. The VISSIM simulation model was then calibrated. According to the proportion of the on-street parking lots into a bus lane, the on-street parking lots conversion simulation model of different scenarios was established, and the influence of different on-street parking lots conversion ratio on traffic efficiency and pollution emission was quantitatively analyzed. Finally, the optimization method based on bus lane network connectivity is discussed. The results indicate that: When the on-street parking lots conversion ratio is approximately 100%, bus speed increases by 21.03%, bus delays decrease by 14.27%, and bus parking instances decrease by 11.31%. Total emissions are negatively correlated with vehicle speed. As the conversion rate of on-street parking increases, the emissions of road segments and the entire road network gradually decrease. At a conversion ratio of 100%, the average total emissions for road segments have the highest reduction rate, decreasing by 4.12%. At a conversion ratio of 50%, the average emission total for the road network shows the largest reduction, falling by 2.88%.

The sexual reproduction of ascomycetes is controlled by the mating-type(MAT) locus. (Pseudo)homothallic reproduction has been hypothesized based on genetic data from Hirsutella sinensis (Genotype #1 of Ophiocordyceps sinensis). In this study, the differential occurrence of the mating-type genes in the MAT1-1 and MAT1-2 idiomorphs, which constitute the genetic control of O. sinensis reproduction, was analyzed in 237 strains and 5 genomes of H. sinensis. The mating-type genes were differentially transcribed in H. sinensis Strain L0106, and the MAT1-2-1 transcript in H. sinensis Strain 1229 was alternatively spliced, with an unspliced intron I containing stop codons; these findings constitute O. sinensis reproduction controls at the transcriptional and coupled transcriptional-translational levels. The occurrence of the mating-type genes and a-/α-pheromone receptor genes differed among the 5 H. sinensis genomes. The differential occurrence and transcription of these genes are inconsistent with self-fertilization under (pseudo)homothallism but suggest self-sterility of H. sinensis, which therefore needs a mating partner to achieve sexual outcrossing under heterothallism or hybridization. Consistent occurrence and transcription of the mating-type genes of both the MAT1-1 and MAT1-2 idiomorphs have been reported in natural and cultivated Cordyceps sinensis, but these findings are insufficient to determine the reproduction mode(s) because of the co-occurrence of >90 fungal species and multiple genomically independent genotypes of O. sinensis. The mutant MAT1-1-1 and α-pheromone receptor transcripts in natural C. sinensis result in the N-terminus or middle-truncated proteins, with changes in hydrophobicity and secondary structures of the proteins, suggesting heterogeneous fungal source(s) of the proteins and hybridization reproduction.

Traditional path planning algorithms have drawbacks in unmanned vehicle path planning, such as low efficiency, unsuitability for dynamic environments, and high computational complexity. To address these issues, this paper proposes a dynamic path planning method for unmanned vehicles that combines the A* algorithm with an improved Dynamic Window Approach (DWA). Firstly, a collision risk function is incorporated into the DWA algorithm to evaluate scores based on the braking distance corresponding to the current vehicle speed and the distance to obstacles, determining whether timely braking or obstacle avoidance is feasible. The earlier the braking or obstacle avoidance, the higher the score, thereby enhancing the evaluation algorithm of the DWA. Secondly, the key points extracted by the A* algorithm are used as temporary target points for the DWA algorithm, reducing the eight search directions to five. Finally, the key points of the A* algorithm’s path are set as the temporary end points for the DWA algorithm, integrating the two algorithms to plan a smoother curved path that can avoid unknown and dynamic obstacles. Simulation data demonstrates that compared to traditional artificial potential field methods, RRT, and Dijkstra’s algorithm, the new fusion algorithm reduces time by 11.71 seconds, a decrease of 6.9%, and shortens path length by 3.093 meters, a reduction of 4.16%, while increasing average linear velocity by 2.9%. The proposed algorithm ensures smoother paths while also making paths more rational and efficient

This paper aims the automatic ball balancers (ABBs) used in passive balancing devices for suppressing vibration of the eccentric rotor. The system model describes which equipped with a skew-mounted ABB with angular deviation. The dynamic equilibrium equations of the system are deduced from the perspective of three-dimensional (3D) dynamics. The results obtained are consistent with those derived from the Euler-Lagrange equations. It is exciting that the spatial dynamics method reveals the spatial geometric characteristic of dynamic balance positioning of the balls when the system is balanced with vibration suppression. The spatial property emerges the perpendicular line from each ball to the rotating spindle of the system must pass through the central axis of the orbit perpendicular to the ABB plane. This characteristic is a general rule that can be used to explain the phenomenon of the stable equilibrium positions of the balls in all previously studied cases.

Proper Post-Activation Performance Enhancement helps to improve athletic performance. This study aimed to investigate the effects of two different velocity loss (VL), 10%VL and 20%VL, on post-activation performance enhancement (PAPE) in 20m sprint performance among sprint athletes. Twenty-four male sprint athletes (100m sprint time: 10.96±0.15 s) were recruited. A randomized crossover experimental design was used for traditional group (TG), 10%VL, and 20%VL interventions. Sprint tests were conducted at the 4th, 8th, 12th, and 16th minutes after the intervention. Two-way repeated measures ANOVA revealed an interaction effect between group and time on 20m sprint performance (F=2.817, p=0.037, partial η²=0.585). Simple effect analyses showed significant differences compared to baseline at the 4th minute for the 20%VL group (P<0.05). Cohen's d values indicated improvement in 10m sprint times at the 8th minute of the rest interval for all three intervention groups (TG: ES=-0.270, 10%VL: ES=-0.038, 20%VL: ES=-0.279). Improvement in 20m sprint times was observed at the 4th minute for the 20%VL group (ES=-0.296) and at the 16th minute for the 10%VL group (ES=-0.276). Compared to traditional PAPE schemes based on 1RM, PAPE schemes based on velocity loss (20%VL) can better induce PAPE effects in sprint athletes.

Blockchain technology (BCT) has the potential for sustainable development, enhancing business efficiency, reducing costs, and strengthening data security. Despite its potential, adoption among small and medium-sized enterprises (SMEs) is low due to the need for significant changes in technology infrastructure and the challenge of interoperability. A cross-sectional survey was done with 226 Hong Kong SMEs. The PLS-SEM results highlighted favorable transformation conditions as the most critical factor for SMEs considering the adoption of BCT. These conditions address both internal and external readiness for adopting the disruptive strategy. Other contributing factors to BCT adoption include trust in BCT developers, perceived usefulness and ease of use, government support, and perceived security. The research results contributed to the literature on disruptive technology acceptance, adoption, transformation conditions, technology readiness, and SMEs’ technology adoption. Government-supported policies and initiatives can promote BCT adoption, including educational programs, case studies, and resources for readiness. Financial support and regulatory frameworks can further encourage adoption. BCT developers can demonstrate the value of their systems, effectively communicate potential ROI and cost savings, and provide user-friendly interfaces to increase SMEs’ intention to adopt BCT.

Effective prediction of wastewater treatment is beneficial for precise control of wastewater treatment processes. The nonlinearity of pollutant indicators such as COD and TP makes the model difficult to fit and has low prediction accuracy. The classical deep learning methods have been shown to perform nonlinear modeling. However, there are enormous numerical differences between multi-dimensional data in the prediction problem of wastewater treatment, such as COD above 3000 mg/L and TP around 30 mg/L. It will make current normalization methods challenging to handle effectively, leading to the training failing to converge and the gradient disappears or exploding. This paper proposes a multi-factor prediction model based on deep learning. The model consists of a combined normalization layer and a codec. The combined normalization layer combines the advantages of three normalization calculation methods: z-score, Interval, and Max, which can realize the adaptive processing of multi-factor data, fully retain the characteristics of the data, and finally cooperate with the codec to learn the data characteristics and output the prediction results. Experiments show that the proposed model can overcome data differences and complex nonlinearity in predicting industrial wastewater pollutant indicators and achieve better prediction accuracy than classical models.

Background: Human papillomavirus (HPV) infection plays a key role in the development of cervical cancer that ranks as the third most common gynecological cancer in China. We attempt to investigate the age and genotype-specific prevalence of HPV DNA in western Chinese females. Methods: A total of 301,880 woman were recruited from 4 different regions of western China. Routine cervical samples were collected and HPV screening was performed using 21 HPV Genotyping test (Hybribio). The overall prevalence, age-specific prevalence, and genotype distribution were analyzed. Results: The overall prevalence of HPV was 18.01%. The high-risk HPV infection rate was 79.14%, the low-risk HPV infection rate was 12.56%, and the mixed HPV infection rate was 8.30%. The most common 4 HR HPV subtypes were HPV-52, 16, 58 and 53, which accounted for 20.49 %, 19.93 %, 14.54 % and 10.01 %. In LR HPV genotype, HPV-6 ranked the highest (28.17 %), followed by HPV-81 (9.09 %), HPV-11 (3.78 %). HPV genotype subgroup analysis also showed that single-type infections had the highest prevalence rate (77.26%) among HPV positive individuals. Among muti-infection genotype, double infection was most common with frequencies of 76.04%. Conclusion: This large report shows that the overall prevalence of HPV was high in China, whose distribution exhibits different patterns across different particular age and regions. Viral genotypes HPV53, 6 were are frequently detected in this population, which is worth of significant clinical attention.

Prevalence of overweight and obesity are escalating globally among the general population. However, there are limited evidence on the trends and prevalence of overweight /obesity in the military setting. Increased rates of injuries, low work productivity, incurred higher healthcare costs and prematurely discharge from service are consequences of overweight/obesity among the military. Therefore, we aimed to systematically describe the trends and prevalence of overweight and obesity in the military population, by regions and military service branches. Databases including PubMed, Scopus, Web of Science and Google Scholar were used. Inclusion criteria were military population (inclusive of all service branches) with BMI reported as the overweight/obesity indicator. Population related to military but not exclusively military personnel such as the retirees, the veterans and their dependents were excluded. From the 27 included studies, 13 were published between year 2010 to 2014 and half were conducted in the United States. Overall, studies showed increasing trend in the prevalence of overweight (30% to 50%) and obesity (2% to 30%); only one study showed a decreasing trend of 0.9% and 0.6% for the prevalence of overweight and obesity respectively. However, the rates of increment differed between countries, where Asian countries demonstrated lower overweight prevalence compared to the United States and the European countries. In conclusion, the military population is not protected from overweight and obesity. Interventions should be implemented to prevent overweight / obesity among the military personnel.

In today's highly digitized and globalized financial environment, the need to protect payment systems from risk is more urgent than ever. Artificial intelligence (AI) technology is rapidly becoming a key tool in this space, with machine learning algorithms, big data analytics, and real-time monitoring enabling AI to effectively detect and prevent fraudulent activity, optimize risk management processes, and deliver intelligent services. AI not only improves the security and efficiency of payment systems, but also significantly improves customer satisfaction and loyalty. With the continuous development of AI technology and financial payment technology, the financial payment industry will usher in more innovations and changes in the future, further optimizing the payment process, improving payment efficiency, and ensuring payment security.

China is a traditional agricultural country, and the integration of rural industries has become an essential policy direction for the current strategy of agricultural modernization in China. In recent years, the agricultural industrial chains across various regions of China have consistently expanded and extended. The multifunctionality of agriculture is continuously unearthed, and the principal entities managing agriculture have become increasingly diversified and have grown significantly. New industries and forms in agriculture emerge incessantly. Accurately and profoundly understanding the inherent features of the integration of industries in rural China, establishing a scientific and rational measurement index system in line with the current status and development goals of rural China, and employing appropriate measurement methods to assess its development level and process, is instrumental in comprehending the level of integrated development in various regions. This aids in identifying challenges in the developmental process and proposing targeted developmental strategies. Hence, this paper, rooted in the integration of rural industries, cross-industry, industry extension, industry agglomeration, and industry penetration, sets up an measurement index system. Using provincial panel data from 2011 to 2020, the paper measures the level of integrated development in rural industries across China and its 31 provinces. Based on the measurement results, further techniques such as kernel density estimation and Gini coefficient decomposition have been used to analyze the spatial distribution characteristics and dynamic trends of the integrated development of rural industries in China. Research indicates that during the sample period, the overall level of integrated development in rural industries in various provinces in China has shown an upward trend. Development among the eastern, central, and western regions is highly uneven, but this disparity has been gradually narrowing in recent years. Furthermore, the levels of integrated development in different provinces exhibit significant spatial agglomeration effects. The development level of neighboring regions significantly impacts the province's development status. In the process of integrated development of rural industries in China, there's a trend where "it's easier to downgrade than to upgrade," with very few regions achieving leapfrog development.

This study investigates the spatial and temporal dynamics of Paomo restaurants in Xi'an's central urban area from 2012 to 2023, leveraging Point of Interest (POI) data through a series of sophisticated analytical techniques. Methods including nearest neighbor distance, kernel density estimation, and band set statistical analysis were employed to thoroughly examine the evolutionary patterns and key drivers influencing the spatial distribution of these eateries. Our results highlight a notable trend of expansion from the central city to the periphery, characterized by significant spatial agglomeration. Initially concentrated in the city center, the distribution of Paomo restaurants has progressively shifted towards multiple distinct cores, reflecting the dual influence of urban policy initiatives and the dynamics of market competition. Furthermore, the research identifies several pivotal factors shaping this spatial distribution, particularly transportation access, residential quality of life, and the availability of commercial services. These findings demonstrate the profound effects of urban spatial reconfiguration and socioeconomic development on the specialized catering industry. The insights gleaned from this analysis offer valuable guidance for urban planners and policymakers, providing strategic recommendations for the spatial planning of specialty catering services to optimize urban layouts and foster sustainable economic progress.

Amid escalating urbanization, devising rational commercial space layouts is a critical challenge. Leveraging machine learning, this study uses a Back-propagation (BP) neural network to optimize commercial spaces in Weinan City's central urban area. The results indicate an increased number of commercial facilities with a trend of multi-centered agglomeration and outward expansion. Based on these findings, we propose a strategic framework for rational commercial space development emphasizing aggregation centers, development axes, and spatial guidelines. This strategy provides valuable insights for urban planners in small and medium-sized cities in the Yellow River Basin and metropolitan areas, ultimately showcasing the power of machine learning in enhancing urban planning.

This paper investigates the evolution of microstructures and precipitations of an ultra-low iron alloy 625 subjected to long term aging treatment by scanning electron microscope (SEM) and X-ray diffraction(XRD). Use ASTM G28A acid Fe3(SO4)2 erosion to represent intergranular corrosion weightlessness and corrosive morphology. The result shows that alloy at 750C by aging treatment for 40h, precipitated γ'' phase in the grain boundary. In high density area of γ'' phase, occurs γ'' phase to δ phase degeneration transformation by aging treatment for 200h and the needle-like δ phase becomes more with time prolonged. And γ'' phase degenerated to δ phase completely until treated for 1000h. The sample which has aging treatment tends to have intergranular corrosion and mainly because alloy element spreading leads to dilution area and grain boundary precipitated phase, plus interlaced δ phase’s dissolving, which makes sample grain particle fall off and this results in apparent weightlessness. The weightlessness rate(WLR) is related with precipitated volume score. With aging sensitization time change, can be described by Johnson-Mehl-Avrami equation, i.e.: $WLR=44.32\left[1-\text{exp}\left(-\frac{t}{10.99}\right)\right]+44.62\left[1-\text{exp}\left(-\frac{t}{327.8}\right)\right]+1.267\left(mm/a\right)$

The escalation of mining activities in the karst regions of Guizhou Province has heightened the occurrence of water-inrush incidents in deep coal mines. This study focused on water-inrush phenomena within the Xinhua mining area of Jinsha County, Guizhou Province, aiming to investigate the sources of these incidents. The findings indicated that the overlying limestone of the Changxing Formation in the coal seam served as a vulnerable aquifer under certain conditions, leading to water inrushes. The analysis of the spatiotemporal distribution patterns of water-inrush incidents at the working face indicated that previous mining operations damaged the shallow Changxing Formation limestone, resulting in the accumulation of goaf water and the formation of numerous mining-induced fractures. These fractures served as rapid conduits for water inrushes from both atmospheric precipitation and underground sources at the deep working face. The examination of surface water and mine water quality demonstrated that both exhibited similar characteristics, predominantly featuring bicarbonate, sulfate, and sodium compositions. Investigation into the relationship between mine water inflow and atmospheric precipitation established that atmospheric precipitation influenced the mine water supply cycle, with a replenishment period of ~10 months during the operational phase of the Jinyuan Coal Mine and about one month post-closure. The fractures induced by mining activities within the Changxing Formation limestone facilitated water flow, with atmospheric precipitation serving as the primary water source for the mine. This study offered a valuable scientific foundation for addressing water-related damage resulting from atmospheric precipitation in mines susceptible to water inrushes under analogous hydrogeological conditions.

Oriental lacquer, a natural and renewable polymeric coating, comes from the sap produced by lacquer trees. For practical application, oriental lacquer must be refined to reduce excess water and enhance its quality. In this study, drying oils were blended with oriental lacquer during the refining process to prepare an oil-modified refined lacquer (OMRL). The type and adding amount (0, 10, and 20% by wt.) of drying oils for wood coatings utilization were evaluated. Rhus succedanea oriental lacquer is composed of 54.1% urushiols, 34.3% water, 7.2% plant gum, and 4.4% nitrogenous compounds, and drying oils, including tung oil (TO), linseed oil (LO), and dehydrated castor oil (DCO) were used as materials in this study. The results show that the drying oil acts as a diluent, which reduces the viscosity and enhances the workability and could shorten the touch-free drying time and speed up the hardened drying of the OMRL. The results also indicate that the hardness, mass retention, Tg, tensile strength, abrasion resistance, and lightfastness of OMRL films decrease as more drying oils are blended. Conversely, the bending resistance, elongation at break, impact resistance increase, and particularly, the gloss, is greatly improved through the blending of more drying oils. In conclusion, the LO-modified refined lacquer (RL) has the highest film gloss and the DCO-modified RL has the shortest drying time for coating; otherwise, the film properties are similar among the three types of drying oil.

In this study, we evaluated the effects of Cyclosporine A (CsA) on Lipopolysaccharide (LPS)-induced cytokine production in the genital tract of female rabbits. Twelve sexually mature and healthy female rabbits were randomly divided into four groups (n = 3 each). The rabbits in the LPS group were given an intrauterine infusion of Escherichia coli LPS (4 mg/kg body weight (BW)). Rabbits in the CsA group were given CsA (20 mg/kg BW). Rabbits in the LPS + CsA group were given LPS (4 mg/kg BW) and CsA (20 mg/kg BW). The control group received only LPS and CsA carrier. The gene expression and protein levels of pro- and anti-inflammatory cytokines were observed using qRT-PCR and immuno-histochemical (IHC) assay, respectively. Our study showed that IL-1β, IL-6, IL-8, TNF-α, IFN-γ, IL-4, IL-10, IL-13, and TGF-β were expressed in female genital organs. The LPS challenge increased the mRNA expression of IL-6 and TNF-α in the uterine body and IL-1β in the uterotubal junction compared to the control group. CsA increased the basal mRNA expression of anti-inflammatory cytokines (i.e., IL-4 in the uterine body, uterotubal junction, and oviductal ampulla; IL-10 in the cervix, oviductal isthmus, and ampulla; and TGF-β in the uterotubal junction and oviductal ampulla) and pro-inflammatory cytokines (i.e., IL-6 and IL-8 in the cervix; IL-1β in the oviductal isthmus; TNF-α in the oviductal ampulla; and IFN-γ in the uterine body compared to the control group). In addition, CsA inhibited the mRNA expression of pro-inflammatory cytokines, such as IL-6 in the uterine body, uterotubal junction, and oviductal isthmus; TNF-α in the uterine body; and IFN-γ in the uterotubal junction and oviductal isthmus induced by the LPS challenge. The IHC assay showed the LPS-induced increase in protein production of IL-6 in the uterine body and oviductal isthmus. CsA increased the protein production of IL-10 in the cervix, uterine body, oviductal ampulla, and isthmus. Moreover, CsA decreased the protein production of IL-6 in the uterine body and oviductal isthmus induced by LPS.

Quantum nonlocality represents correlation properties between subsystems of a composite quantum system, usually including the four types: Bell nonlocality, steerability, entanglement, and quantum correlation (quantum discord). Given a basis $e_{AB}=\{|e_{ij}\>\}_{i\in[d_A],j\in[d_B]}$ for the Hilbert space $\H_A\otimes \H_B$ of a bipartite system $AB$, a density operator $\rho^{AB}$ (quantum state) of $AB$ can be represented as a $d_Ad_B\times d_Ad_B$ matrix $\hat{\rho}_{e_{AB}}=[\]$, called the density matrix of a density operator $\rho^{AB}$. A natural question is what is the relationship between the quantum nonlocality of a density operator $\rho^{AB}$ and its corresponding density matrix $\hat{\rho}_{e_{AB}}$? In this work, we discuss the relationships between quantum locality and basis, and prove that one type of quantum locality of density operators and that of their density matrices under a basis are the same if and only if the chosen basis is the tensor product of the bases of subsystems. Consequently, different bases define different quantum nonlocality density operators.

The quality of healthcare services is a very important indicator of social welfare in developed and emerging countries. Good quality levels are critical to ensuring patient safety, improving health outcomes, increasing patient satisfaction, optimizing resource utilization, and meeting regulatory requirements. The stable and sustainable operation of medical institutions urgently requires the establishment of a reliable and effective medical quality performance evaluation platform. However, the complexity of the evaluation process, involving numerous evaluators and the consideration of different subjective and objective criteria, poses significant challenges and essentially constitutes a group multi-criteria decision-making problem. This article uses the overall medical environment of the institution, medical service attitude, medical security, administrative service measures, etc. as measurement standards to deal with this challenge. It proposes a medical service quality measurement model suitable for both qualitative and quantitative analysis. In view of the heterogeneity of information, the two-tuple fuzzy language calculation method is introduced to enable evaluators to skillfully manage diverse information and effectively avoid potential information omission problems in the subjective evaluation integration process. The effectiveness and feasibility of the model were demonstrated by applying it to the operational framework of a medical institution in central Taiwan.

Background and Objectives: Cancer as the second leading cause of death in the United States poses a huge healthcare burden. Barriers to access to advanced therapies influence the outcome of cancer treatment. In this study, we examined whether insurance types affect the quality of cancer clinical care regarding access to an important monoclonal antibody, ramucirumab. Materials and Methods: Data for 13,340 cancer patients with Purchased or Medicaid insurance from the All of Us Database were collected for this study. The Chi-square test of proportions was employed to determine the significance of patient cohort characteristics and ramucirumab usage between Purchased and Medicaid insurance groups. The independent t-test was utilized to assess the influences of other determinants on insurance types. Results: Cancer patients who are African American, with lower socioeconomic status, or with lower educational attainment are more likely to be insured by Medicaid. Analysis of survey questions demonstrated the relationship between income and education level with insurance type as Medicaid cancer patients were less likely to receive primary care and specialist physician access and more likely to request lower cost medications. In addition, those with Medicaid insurance were identified to have poorer access to expensive therapeutics like ramucirumab compared to those with Purchased insurance.  Conclusions: The inequities of the US healthcare system are observed for cancer patient care; access to physicians and therapeutics are highly varied and dependent on insurance types. Socioeconomic status determines insurance type, which unfortunately generates a significant impact on cancer treatment and disease outcome.

With the realization of the Grand Canal's full water supply and the strong pursuit of green and low-carbon transportation in contemporary society, the value of the Grand Canal's water transport has been further affirmed, and its coordinated development with other transportation modes has become inevitable and important. This paper analyzes and combs through the characteristics, development status and existing problems of Grand Canal water transport and other transport modes in depth, and takes Jiangsu as an example. A collaboration model of Grand Canal water transport and other transport modes was built and their collaboration degree has been calculated. It is believed that the coordinated development of Grand Canal water transport and other transport modes can be greatly promoted via four aspects: optimizing the construction and governance of Grand Canal water transport, building an integrated management platform of transport modes, improving the integrated transport network structure, and promoting the deep integration of integrated shipping and tourism.

This study used Dutch potatoes at the end of dormancy as the material to explore the impact of menthol (0.2 and 0.5 g/kg based on potato mass) treatment on sprouting inhibition and potato quality. The findings revealed that a menthol concentration of 0.5 g/kg effectively inhibited potato tuber sprouting and significantly reduced glucoside alkaloids production. After a storage period of 15 days, the sprouting percentage and glucoside alkaloids content of potatoes treated with 0.5 g/kg menthol were observed to be significantly lower at 4.17% and 68.63 mg/kg, respectively, compared to the control group which exhibited values of 100% and 282.01 mg/kg, respectively (P < 0.05). Throughout the storage period, 0.5 g/kg of menthol promoted respiration, reduced malondialdehyde production in potatoes, inhibited polyphenol oxidase activity, and slowed down tissue browning. Additionally, it mitigated the decline in starch and soluble protein content, inhibiting the accumulation of reducing sugars.

This study explores fault-tolerant consensus in leader-following heterogeneous multi-agent systems, focusing on actuator failures in uncrewed aerial vehicles (UAVs) and uncrewed ground vehicles (UGVs). An optimization-based fault-tolerant consensus algorithm is proposed. The algorithm utilizes the Euler-Lagrange formula to ensure system consistency under actuator failures, with the Lyapunov stability theory proving the asymptotic stability of the consistency error. The algorithm is applied to heterogeneous multi-agent systems of UAVs and UGVs to derive optimal fault-tolerant consensus control laws for each vehicle type. Simulation experiments give evidence for the feasibility of the proposed control strategy.

Civic participation is of great significance to urban management decision-making. In order to facilitate citizens to participate in city management decision-making, this paper proposes a large-scale group decision-making (LSGDM) method based on multi-granular probabilistic linguistic preference relations (MG-PLPRs). First, each decision maker selects a language terms set from the multi-granularity language terms set to represent individual preference relations and the MG-PLPRs are obtained by statistical calculation to represent sub-group’s preferences information. Then, an optimization model based on the expected consistency of PLPR and consensus measure of groups is established to achieving consensus reaching processes, which can ensure satisfactory individual consistency and group consensus. Finally, the validity and applicability of the proposed method is verified by a case of a city "shared garden" site selection with the participation of citizens.

This paper proposed an optimal tracking control scheme through adaptive dynamic programming(ADP) for a class of partially unknown discrete-time nonlinear systems based on radial basis function neural network(RBF-NN). In order to acquire the unknown system dynamics, we use two RBF-NNs, the one is used to construct the identifier, and the another is used to directly approximate the steady-state control input, where a novel adaptive law is proposed to update neural network weights. While the optimal feedback control and the cost function are derived via feedforward neural networks approximating, it is proposed to regulate the tracking error, the critic network and the actor network are then trained online to obtain the solution of the associated Hamilton–Jacobi–Bellman (HJB) equation being built under the ADP framework. Simulations verify the effectiveness of the optimal tracking control technique using the neural networks.

Base on building information modeling(BIM) plus with Robotic process automation (RPA) technology is rapid development in smart building operations and maintenance (O&M). RPA is a workflow-based automated execution tool that is particularly well suited for replacing manual execution of simple and repetitive tasks using computer systems. The use of RPA technology can saves man-hours and increases productivity, which is important for the automation of building operations and maintenance operations.. The BIM technology, as an advanced technology in the construction industry, it can provide new ideas and methods for building operation and maintenance based on its visualization characteristics. That’s integrating RPA with BIM technology which will enhance the digitalization and virtualization of smart building operation and management. In this article will first introduce the features of RPA and BIM technology and then discuss the technical roadmap for remote automated operation and maintenance of smart building equipment room to implemention a low-cost and high efficient building equipment room operation and maintenance solution.

Purpose: We evaluated the outcomes of fluid-gas exchange (FGE) for long-term flap closure of idiopathic macular hole (MH) after the inverted internal limiting (ILM) flap technique. Methods: We included eyes showed flap closure without complete MH closure, connection of the apart macular tissue, 1 month postoperatively after the inverted ILM flap technique. The eyes stayed at flap closure at 2 months postoperatively further underwent in-office FGE with 16% C3F8. Results: Among 10 eyes, 5 eyes (50%) showed flap closure at 2 months postoperatively further underwent FGE for complete MH closure while the remaining 5 eyes (50%) progressed directly at 2 months postoperatively. The improvement in vision of all flap closure from baseline was significant (p=0.015), with the mean baseline vision was 1.19 [Snellen equivalent (SE), 20/307] ± 0.52 logMAR and the mean final vision being 0.63 (SE, 20/85) ± 0.38 logMAR. The group that underwent FGE showed a better final vision of 0.45 (SE, 20/75) ± 0.23 logMAR than the group that didn’t undergo FGE (0.81 [SE, 20/128] ±0.44 logMAR). All eyes achieved complete MH closure, including the eyes that underwent FGE in a mean period of 5.60 months (range 3-10 months) after the inverted ILM flap technique. The eyes that underwent FGE achieved higher rate of foveal restoration [complete external limiting membrane (ELM): 80%; complete ellipsoid zone (EZ): 60%] than those that didn’t receive FGE (complete ELM: 40%; complete EZ: 10%). Conclusions: Eyes that underwent FGE accelerated complete MH closure and showed better final vision and fovea l restoration.

We propose a novel protocol to build a maximally entangled state based on controlled-not (CNOT) gates. In particular, we give detailed steps to construct maximally entangled state for 4-, 5-, and 6-qubit systems. The advantage of our method is the simple algebraic structure which can be realized via current experimental technology.

Both fibrosis and cirrhosis of the liver are the end results of most kinds of chronic liver damage and present a common but difficult clinical challenge throughout the world. The inhibition of the fibrogenic, proliferative, and migratory effects of hepatic stellate cells (HSCs) has become an experimental therapy for preventing and even reversing hepatic fibrosis. Furthermore, a complete understanding of the function of non-coding RNA-mediated epigenetic mechanisms in HSC activation may improve our perception of liver fibrosis pathogenesis. This review focuses on an evolving view of molecular mechanisms in which HSC activation by miR-29a signaling may moderate their profibrogenic phenotype, thus supporting the use of miR-29a agonists as a potential therapy for treating liver fibrosis in the future.

Cadmium(Cd) is a highly toxic and cumulative environmental pollutant. Siderophores are heavy metal chelators with high tolerance to heavy metals such as Cd. Furthermore, ryegrass (Lolium perenne L.) has potential remediation capacity for soils contaminated by heavy metals. Consequently, using ryegrass alongside beneficial soil microorganisms that produce siderophores may be an effective means to remediate soils contaminated with Cd. In this study, Bacillus strains WL1210 and CD303 that were previously isolated from the rhizospheres of Nitraria tangutorum in Wulan and Peganum harmala L in Dachaidan, respectively, both arid sandy environments, were evaluated for heavy metal pollution mitigation. The results indicate that both strains of Bacillus exhibit favorable biological characteristics and stress resistance, and they are both producers of siderophores, which promote the growth of ryegrass under Cd stress.

Pyrethroid pesticides (PYRs) as the third most widely used pesticides, following organophosphorus and carbamate pesticides, which are of significant importance in the analysis and detection of vegetables. However, the current pretreatment technology for PYRs confronts challenges of difficult separation and low enrichment efficiency, resulting in a cumbersome and time-consuming pretreatment process with poor selectivity. Here, a simple and efficient magnetic solid-phase extraction (MSPE) strategy was developed to simultaneously purify and enrich five PYRs in vegetables, with the magnetic covalent organic framework nanomaterial COF-SiO2@Fe3O4 as an adsorbent. The COF-SiO2@Fe3O4 was prepared by a simple solvothermal conditions method, using Fe3O4 as magnetic core, benzidine and 3,3,5,5-tetraaldehyde biphenyl as two building units. COF-SiO2@Fe3O4 could effectively capture the targeted PYRs by virtue of its abundant π-electron system and hydroxyl groups. The impact of various experimental parameters on extraction efficiency was investigated to optimize the MSPE conditions, including adsorbent amount, extraction time, elution solvent type and elution time. Subsequently, method validation was conducted under the optimal conditions in conjunction with gas chromatography-mass spectrometry (GC-MS). Within the range of 5.00–100 μg·kg-1 (1.00–100 μg·kg-1 for bifenthrin and 2.5–100 μg·kg-1 for fenpropathrin), the five PYRs exhibited a strong linear relationship, with determination coefficients ranging from 0.9990 to 0.9997. The limits of detection (LODs) were 0.3–1.5 μg·kg-1, and the limits of quantification (LOQs) were 0.9–4.5 μg·kg-1. The recoveries were 80.2–116.7% with relative standard deviations (RSDs) below 7.0%. Finally, COF-SiO2@Fe3O4, NH2-SiO2@Fe3O4 and Fe3O4 were compared as MSPE adsorbents for PYRs. The results indicated that COF-SiO2@Fe3O4 was an efficient and rapid selective adsorbent for PYRs. This method holds promising prospects for the determination of PYRs in real samples.

Sympatric distribution and temporal overlap of cryptic zooplankton species pose a challenge to the framework of the niche differentiation theory and the mechanisms allowing competitor coexistence. We applied the methods of phylogenetic analysis, DNA taxonomy and statistical analysis to study the temporal distribution patterns of cryptic B. calyciflorus species, an excellent model, in three lakes, and to explore the putative mechanisms for their seasonal succession and temporal overlap. The results showed that in the warm-temperate Lake Yunlong, B. fernandoi and B. calyciflorus s.s. underwent a seasonal succession, which was largely attributed to their differential adaptation to water temperature. In the subtropical Lake Jinghu, B. fernandoi, B. calyciflorus s.s. and B. dorcas exhibited both seasonal succession and temporal overlap. Seasonal successions were largely attributed to their differential adaptation to temperature, and temporal overlap resulted from their differential responses to algal food concentration. In the tropical Lake Jinniu, B. calyciflorus s.s. persisted throughout the year, and overlapped with B. dorcas for 5 months. Temporal overlap resulted from their differential responses to copepod predation. These results indicated that the temporal distribution pattern of cryptic B. calyciforus species and the mechanism allowing competitor coexistence vary with different climate zones.

Ionospheric delay has been a critical issue that limits the accuracy of GNSS precise positioning and navigation for single-frequency users, especially in mid- and low-latitude regions where irregularity of ionosphere is often significant. Kriging spatial interpolation techniques have been recently introduced to model the spatial correlation and variability of ionosphere, which intrinsically assume that the ionosphere field is stochastically stationary but does not take the random observational errors into account. In this paper, by treating the spatial statistical information on ionosphere as prior knowledge and based on TEC semivariogram analysis, we use Kriging techniques to spatially interpolate TEC values. By assuming that the stochastic models of both the ionospheric signals and measurement errors are only known up to some unknown factors, we propose a new Kriging spatial interpolation method with unknown variance components for both the signals of ionosphere and TEC measurements. Variance component estimation has been integrated with Kriging to reconstruct regional ionospherical delay. The method has been applied to data from the Crustal Movement Observation Network of China (CMONOC) and compared with the ordinary Kriging and polynomial interpolations with spherical cap harmonic functions, polynomial functions and low-degree spherical harmonic functions. The results have shown that the interpolation accuracy of the new proposed method is better than the ordinary Kriging and polynomial interpolation by about 1.2 TECU and 0.7 TECU, respectively. The root mean squared error of the proposed new Kriging with variance components is within 1.5 TECU and is smaller than those from other methods under comparison by about 1 TECU. When compared with ionospheric grid points, the mean squared error of the proposed method is within 6 TECU and smaller than Kriging, indicating that the proposed method can produce more accurate ionospheric delays and better estimation accuracy.

Carbon dots are carbon based nanoparticles, which have the characteristics of simple preparation process, photoluminescence, biocompatibility, adjustable surface function, water solubility, and low toxicity. They are widely used in biological applications such as imaging, biosensing, photocatalysis, and molecular transfer. It has also aroused great interest among researchers in agriculture and has made significant progress in improving crop growth and production. This review presents the physiological functions of carbon dots for crop growth and development, photosynthesis, water and nutrient absorption, and abiotic stress resistance and their applications in improving ecological environment and agriculture as biosensors, and the future application prospects and research directions of carbon dots in agriculture were prospected.

Saikosaponin (SS) a is a compound with various pharmacological properties and easily degraded into SSb1 and SSg in acid condition. In present work another two new degradation products of SSa formed under acid hydrolytic condition were detected and isolated by analytical and semi-preparative liquid chromatography technology, furthermore their structures were characterized as hydroxyl-saikosaponin a and SSb2 by spectral analysis, which is not only essential in stability-indicating method development and validation but also could be used as a worst case to assess the analytical method performance of SSa. Moreover their structural transformation pathways were also proposed.

Molecular hydrogen (H2) has been shown to have antioxidant and anti-inflammatory activities that may reduce the development and progression of many diseases. In this study, Hydrogen-rich water (HRW) was obtained by reacting hybrid magnesium-carbon hydrogen storage materials with water. Then the effects of intake of HRW on the activities of xenobiotic-metabolizing enzymes, membrane transporters, and oxidative stress in rats were investigated. Rats were given HRW ad libitum for 4 weeks. Results showed that intake of HRW had no significant effect on the activities of various cytochrome P450 (CYP) enzymes (CYP1A1, 1A2, 2B, 2C, 2D, 2E1, 3A, 4A), glutathione-S-transferase and UDP-glucuronosyltransferase. Except for a slight lower plasma glucose concentration, intake of HRW had no effect on other plasma biochemical parameters in rats. P-Glycoprotein and multidrug resistance-associated protein (Mrp)2 protein expressions in liver were elevated after intake of HRW. However, HRW had no significant effects on glutathione, glutathione peroxidase, or lipid peroxidation in liver. Results from this study suggest that consumption of HRW may not affect xenobiotic metabolism or oxidative stress in liver. However, intake of HRW may increase the efflux of xenobiotics or toxic substances from the liver into bile by enhancing the expression of p-glycoprotein and Mrp2 protein.

Real-time object detection remains a pivotal topic in the realm of computer vision. Balancing the accuracy and speed of object detectors poses a formidable challenge for both academic researchers and industry practitioners. While recent transformer-based models have showncase the prowess of the attention mechanism, delivering remarkable performance improvements over CNNs, their computational demands can hinder their effectiveness in real-time detection tasks. In this paper, we elect to use YOLOX as our robust starting point and introduce a series of effective enhancements, culminating in a new high-performance detector named YOLOAX. To further exploit the power of the attention mechanism, we devise multi-dimensional attention-based modules that activate CNNs, emphasizing the most pertinent regions and bolstering the capacity to learn the most informative image representations from feature maps. Moreover, we introduce a novel leading label assignment strategy called STA, along with a groundbreaking loss function named GEIOU Loss, to further refine our detector's performance. We provide extensive ablation studies on the COCO and PASCAL VOC 2012 detection datasets to validate our proposed methods. Remarkably, our YOLOAX is trained solely on the MS-COCO dataset from scratch, without leveraging any prior knowledge, which achieves an impressive 54.2% AP on the COCO 2017 test set while maintaining a real-time speed of 72.3 fps, surpassing YOLOX by a significant margin of 3.0% AP. Our source code and pre-trained models are openly accessible at https://github.com/KejianXu/yoloax.

The objective of this study was to synthesize 9-/13-position substituted berberine derivatives and evaluated their cytotoxic and photocytotoxic effects against three human cancer cell lines. Among all the synthesized compounds, 9-O-dodecyl- (5e), 13-dodecyl- (6e) and 13-O-dodecyl-berberine (7e) exhibited stronger growth inhibition against three human cancer cell lines, (HepG2, HT-29 and BFTC905), in compare with structurally related berberine (1). These three compounds also showed the photocytotoxicity in human cancer cells in a concentration-dependent and light dose-dependent manner. Through flow cytometry analysis, we found out a lipophilic group at 9-/13-position of berberine may have facilitated its penetration into test cell and hence enhanced its photocytotoxicity on human liver cancer cell HepG2. Further, in cell cycle analysis, 5e, 6e and 7e induced HepG2 cells to arrest at S phase and caused apoptosis upon irradiation. In addition, photodynamic treatment of berberine (1) and its derivatives 5e, 6e and 7e again showed a significant photocytotoxic effects on HepG2 cells, induced remarkable cell apoptosis, greatly increased intracellular ROS level and the loss of mitochondrial membrane potential. These results over and again confirmed that berberine derivatives 5e, 6e and 7e greatly enhanced photocytotoxicity. Taking together, the test data led us to conclude that berberine derivatives with a dodecyl group at 9-/13-position could be great candidates for the anti-liver cancer medicines developments.

Dry eye syndrome (DES) has become increasingly prevalent due to the prolonged use of digital devices in modern society. Individual supplementation with lutein or docosahexaenoic acid (DHA) demonstrated potential benefits for eye health. This study aimed to investigate the effects of lutein plus DHA complex supplementation on DES, visual function, and memory in healthy individuals. Thirty-four participants, aged 40~60 years, received lutein/DHA complex supplements (containing 10 mg free-form lutein, 200 mg DHA, 30 mg red algae extract (astaxanthin), phosphatidylserine, and vitamin A) for 12 weeks. Ophthalmological examinations and memory tests were carried out, and a questionnaire was administered at weeks 0, 6, and 12 of the study. After 12 weeks of the intervention, the tear break-up time had significantly increased, and intraocular pressure (IOP) had significantly decreased. This suggests that lutein/DHA complex supplementation may reduce the IOP and offer potential benefits for DES, as indicated by improved tear stability.

The rapid growth of the sharing economy has propelled shared mobility to the forefront of attention. The continuous advancement of autonomous driving technology also brings new opportunities and challenges to the shared mobility market. This study comprehensively analyzes the market potential concerning autonomous vehicles (AVs) to provide shared mobility services, utilizing SWOT analysis, PESTLE analysis, and Porter’s Five Forces. The findings reveal that AVs can provide improved shared mobility services by increasing transportation safety, reducing emissions, reducing costs, enhancing traffic efficiency, and increasing customer satisfaction and the profitability of shared mobility services. However, challenges such as technological and policy uncertainties, safety concerns, high initial costs, inadequate public communication infrastructure, and the absence of standardized regulations can hinder the widespread adoption of AVs. The benefits are also restricted with a low market penetration rate of AVs. To promote AVs in the shared mobility market, this study also provides implications for AV stakeholders tailored to the evolving shared mobility market dynamics.

High dimensional statistical analysis for the yield of large-scale circuits is quite difficult due to expensive simulations, especially for the memory circuits with high sigma requirement (e.g., SRAM). In this paper, we developed an efficient sparse additive model to substitute simulations. To fit high sigma region accurately, the modeling center is moved to near failure boundary searched by scaling the shape of sampling function. To solve the model efficiently, the process variables are grouped by standard cells so that the model can be solved by our developed blockwise greedy algorithm. The experiments on the 28nm memory circuits validate that our method achieves high accuracy and efficiency compared with other state-of-art works.

The plethora of bio-functional compounds present in fermented alcoholic beverages like wine, as well as the valorization of bioactives from their wineries/breweries by-products like grape pomace and grape seed, has gained significant interest in the functional foods sector. Wine has always accompanied humanity, for religion or for health. For example, Christians are using wine in the “Holy Communion”, following what Jesus Christ himself did and said during the Last Supper, while the benefits of the wine consumption in moderation was embedded in all Mediterranean civilizations, as it is mentioned by the wise King-Prophet David in his psalms, but also by Hip-pocrates and other wise men, in a Greek-based philosophy of “All things in Moderation” (Cleobulus of Lindos; 6th century BC). In modern times, and after the outbreak of research on wine benefits since the 90’s, when the term “French Paradox” was introduced in the US public during a CBS show, recent evidence has outlined that these benefits are derived by the synergisms of its bio-functional compounds and their digestion-derived metabolites. Within this article, the proposed health benefits of moderate wine consumption, as a functional component of a balanced diet (i.e. the Mediterra-nean Diet), against inflammation-related chronic disorders, is thoroughly reviewed. The various bio-functional compounds of both wine and wineries’ by-products, such as their bioactive phe-nolics, unsaturated fatty acids, polar lipids, and dietary fibers, and their functional antioxidant, anti-inflammatory and antithrombotic health promoting properties are also thoroughly evaluated. The mechanisms of actions and synergism, by which the health benefits are elicited, are also ex-plored. Functional properties of non-alcoholic wine products are also introduced. Emphasis is also given to applications of wineries’ by-products bioactives, as ingredients of bio-functional foods, supplements and nutraceuticals. Limitations and future perspectives for this popular functional alcoholic beverage (wine) ant its rich in bioactives by-products are also addressed. .

Revealing the multidimensional value of cultivated land resources, improving calculation methods, and exploring their spatial distribution characteristics and influencing factors are crucial for the enhancement of natural resource accounting system and the protection of cultivated land resources. This study take Guangxi, China as an example and construct a comprehensive multidimensional value evaluation system for cultivated land resources at the county scale. The income capitalization method, substitution market method, and value equivalent correction method were applied to calculate the economic, social, and ecological values of cultivated land resources in 111 counties. Furthermore, spatial autocorrelation analysis was employed to study their distribution characteristics and influencing factors. The results show that: (1) The total value of cultivated land resources in Guangxi reach 19,729.2 billion yuan, and the average cultivated land value is 5.3511 million yuan/hm2, of which the ratio of economic, social and ecological values is about 6:1:2; (2) The value of cultivated land has a certain distribution pattern in the global space, and the average economic and social value show the spatial distribution patterns of "low in the west and high in the east" and "low in the northwest and high in the southeast" respectively."(3) There is a significant spatial clustering effect of all values of cultivated land resources in local space, with "high-high" and "low-low" clustering. (4) Economic development level is significantly negatively correlated with the ecological value of cultivated land, while has a significant positive correlation with social value; (5) Natural conditions, economic development and agricultural development approaches are the key factors affecting the value of cultivated land resources.

The rapid growth of network services, Internet of Things devices and online users on the Internet have led to an increase in the amount of data transmitted daily. As more and more information is stored and transmitted on the Internet, cybercriminals are trying to gain access to the information to achieve their goals, whether it is to sell it on the dark web or for other malicious intent. Through thorough literature study relating to the causes and issues that are brought from the security and privacy segment of wireless networks, it is observed that there are various factors that can cause the networks to be an insecure; especially factors that revolve around cybercriminals with their growing expertise and the lack of preparation and efforts to combat them by relevant bodies. The aim of this paper is to showcase major and frequent security as well as privacy issues in wireless networks along with specialized solutions that can assist the related organizations or the public to fathom how great of an impact these challenges can bring if every related stakeholder took a step in reducing them. Through this paper it is discovered that there are many ways these challenges can be mitigated, however, the lack of implementation of privacy and security solutions is still largely present due to the absence of practical application of these solutions by responsible parties in real world scenarios.

We study a two-echelon supply chain made up of a supplier and a manufacturer, both of which can reduce their component/product carbon emissions. With the vertical technology spillovers, we explore the optimal decisions of centralized and decentralized supply chains with price dependent demand and propose coordination strategy for the decentralized supply chain. Considering the cost contraction effectiveness of the technology spillovers, the centralized and decentralized game theoretic models of a two-echelon supply chain are developed to investigate optimal decisions of pricing and carbon emissions reduction. Through a systematic comparison and numerical analysis, we show that the profits of both players and the entire supply chain improve with the effect of technology spillovers increasing. Carbon emissions reduction will be taken by various protective measures so that the supplier and the manufacturer who do not innovate can hardly share the results of innovating via the “free-riding” methods when the technology spillover is relatively small. We also propose a revenue-cost sharing contract through bargaining to enhance the performance of the decentralized supply chain.

: Tunnel instability and lining integrity are intimately tied to the creep properties of the surrounding rock. The acquisition of rock mass creep parameters is critical in ascertaining the appropriate timing for lining construction. Nevertheless, creep tests on rock specimens conducted in a controlled setting cannot be straightforwardly extrapolated to rock mass creep analysis. This study performs laboratory-based creep tests on mudstone samples and establishes the corresponding creep constitutive model. Integration of a Mohr-Coulomb element with the Burgers model in series serves to characterise the yield creep behaviour of the rock mass. Additionally, the research outlines a series of 100 orthogonal experiments utilising randomised creep parameters, and formulates a GA-BP neural network inversion model. Employing long-term deformation measurements from the crown and sidewalls of the project site, this study deduces the creep parameters of the mudstone in the investigated tunnel section and examines the prolonged deformation traits of the surrounding rock. Drawing on the deformation traits of the surrounding rock and the forces impacting the primary support and lining structures, this paper evaluates the earliest and latest viable lining casting periods and pinpoints an optimal timing interval for lining implementation. The methodologies employed herein can serve as a benchmark for analogous endeavors internationally.

Abundant of preparatory works have recognized that fluorescent sensors based on 8-aminoquinoline are popular tools to detect Zn2+ ions in environmental and biological applications. Along with these studies, researchers started to introduce a variety of carboxamido group into an 8-aminoquinoline molecule in forming 8-amidoquinoline derivatives. Therefore, this systematic review aims to introduce a general overview of the fluorophore 8-aminoquinoline as Zn2+ receptors and to provide comparisons of collected studies that related to 8-amidoquinoline derivatives as fluorophore probe of the sensor. According to PRISMA systematic searches strategy, 13 articles were analyzed for trends, research designs, results and discussion, subject samples, and remarks or conclusions. We found cross-sectional studies with four aspects in zinc sensing that have been targeted; binding studies via titration, detection's limit, interferences studies, and validation of the study. Hence, this paper also included assessments of those criteria and the trends of development of 8-amidoquinoline derivatives based-zinc fluorescent chemosensor. It also showed that most of the researches conducted in China. In conclusion, this study identified various research designs of fluorescent chemosensors based on 8-amidoquinoline prolong with the effectiveness and potential as a recognition probe to assist the detection of zinc. Hence, elucidation of those derivatives essential to be explored because more studies are needed to improve the sensing criteria of the zinc sensor

The use of chimeric antigen receptor (CAR) in natural killer (NK) cells for cancer therapy is gaining momentum, marking a significant shift in cancer treatment. This review aims to explore the potential of CAR-NK cell therapy in cancer immunotherapy, providing a fresh perspective. It discusses the innovative approaches in CAR-NK cell design and engineering, particularly targeting refractory or recurrent cancers. By comparing CAR-NK cells with traditional therapies, the review highlights their unique ability to tackle tumor heterogeneity and immune system suppression. Additionally, it explains how novel cytokines and receptors can enhance CAR-NK cell efficacy, specificity, and functionality. The review underscores the advantages of CAR-NK cells, including reduced toxicity, lower cost, and broader accessibility compared to CAR-T cells, along with their potential in treating both blood cancers and solid tumors.

Developing and utilising of underground space is an vital direction for urban growth. Underground commercial streets, as a significant component of underground space accommodating extensive human social activities, and consequently necessitate the creation of human-scale spaces. In the evolution of urban design development towards greater refinement, applying architectural theories and excessively subjective designs has resulted in a deficiency of human-centered design and a disordered spatial environment. This study merges environmental psychology and architectural theory to determine the appropriate length of spatial scale. Two experiments focusing on spatial perception evaluation were conducted using a virtual experimental platform that featured varying dimensions of spatial scale combinations. These quantified combinations were correlated with perception evaluation, and regression analysis was employed to identify appropriate scale ranges, which were superimposed on the range of length selection. Finally, the optimal length and scale combination for underground commercial street spaces were established, providing a reference for the human-centered design of these environments.

Deficiency of interleukin-1 receptor antagonist (DIRA) is a rare life-threatening autosomal recessive autoinflammatory disease with symptoms including but not limited to osteomyelitis, periostitis, and systemic inflammation. DIRA is developed from the loss-of-function mutations of IL1RN gene that encodes IL-1 receptor antagonist (IL-1RA), leading to the unchecked pro-inflammatory signaling and subsequent systemic inflammation. Thus, Anakinra as the recombinant IL-1RA has become the primary drug to treat DIRA. Although Anakinra has been effective for complete remission of DIRA, it also showed various side effects. To further address its efficacy and safety in treating DIRA, a review of literature was conducted in this study. We have identified 15 papers with 25 patients studied, making it possible to conduct reliable statistical analyses. The literature review found that continual treatment with Anakinra is effective to cause clinical remission of DIRA. Statistical analyses found that after the treatment with Anakinra, patients had improved Hemoglobin, Erythrocyte Sedimentation Rate, and C-reactive Protein levels. All known cytogenetic abnormalities were also analyzed to inform clinicians for genetic screening and rapid diagnosis of DIRA. The results from this study provide a comprehensive view for further improving the treatment of DIRA by Anakinra.

As e-commerce services and Internet technology have rapidly developed in recent years, many services and applications integrating these technologies can now be completed online. These commercial activities include online auctions, online ticketing and online payments. The client shops from the store online, andthe store delivers the goods to the client. The goods can be divided into digital products without entities, as well as actual entities. If it is a physical product, the store will deliver the package to the client through itslogistics. However, there have been many cases of switched goods purchased by clients in recent years. Earlier, some scholars proposed a security mechanism with a subliminal channel for E-cash and digital content. Only the sender and the receiver would know that the secret information was hidden in the signature. So the privacy of this subliminal message couldbe ensured. We apply this concept to the logistics environment to design secure logistics architecture with subliminal messages. The client can check the subliminal message of the received package, and know whether the package has been switched by malicious people. In addition, the proposed scheme also applies sensor technology;the client can check the GPS location, the temperature and humidity at any time during the delivery process. So intelligent logisticswouldthereby be achieved. This paper proposes an intelligent and secure package sensoring logistics system based on a subliminal channel. The proposed architecture uses the related mechanisms tosolve the problems of a logistics system, including how to achieve mutual authentication, data integrity, anti-switch package, package location and status tracing, resisting replay attacks, forward and backward secrecy, and non-repudiation issues.

As a precious natural resource, forests are being destroyed. In previous studies, there is a lack of interactive assessment of its distribution that comprehensively considers multiple external disturbances. This paper takes the Barcelona Metropolitan Region as an example. Based on remote sensing, it analyzes the development process of the forest from 2006 to 2018 through multiple landscape indicators, and OLS models were established to analyze variables that have direct and indirect effects on forest distribution. In addition, the ecological structure of the forest was analyzed based on NDVI. It was found that the forest area is the largest but has been decreasing, becoming more complex in distribution structure. Much of the forest was converted to agricultural land and grassland. The green quality of forests was increasing, and the broad-leaved forest, the second largest area, contributes the most. NDVI is the most important positively correlated variable, and daytime surface temperature is an important inverse factor related to NDVI. In addition, NDBI is also a negative condition that inhibits forest development. In conclusion: The BMR forest area is decreasing and becoming more fragmented. NDVI and daytime LST are the two most significant factors. Climate warming may lead to worse forest development.

Keywords: mHealth; peritoneal dialysis; functionality; usability

This study introduces an advanced dual-mode composite attitude control framework for reusable launch vehicles (RLVs), underpinned by an enhanced particle swarm optimization (PSO) algorithm. This innovative strategy is tailored to meet the stringent demands for precision and robust anti-interference capabilities across the entire flight envelope of RLVs. The research commences with the formulation of a comprehensive attitude dynamics model and diverse heterogeneous actuator representations, meticulously crafted to reflect the distinct phases of RLV flight. Building upon this foundation, a synergistic control paradigm is engineered, integrating PID and fuzzy PID controllers, complemented by a refined fitness evaluation function. The crux of the study is the application of an upgraded PSO algorithm to fine-tune the controllers' weighting coefficients, culminating in an optimized dual-mode composite attitude control system. A series of comparative simulation analyses are meticulously executed to appraise the system's responsiveness, stability, precision, and resilience to interference. The findings unequivocally substantiate the superior performance of the proposed control system, affirming its substantial contribution to the advancement of RLV attitude control.

Few-shot object detection (FSOD) aims to address the challenge of requiring a substantial amount of annotations for training in conventional object detection, which is very labor-intensive. However, existing few-shot methods achieve high precision with the sacrifice of time-consuming for exhaustive fine-tuning, or take poor performance in novel-class adaptation. We presume the major reason is that the valuable correlation feature among different categories is insufficiently exploited, hindering the generalization of knowledge from base to novel categories for object detection. In this paper, we propose Few-Shot object detection via Correlation-RPN and Transformer Encoder-Decoder (CRTED), a novel training network to learn object-relevant features of inter-class correlation and intra-class compactness while suppressing object-agnostic features in the background with limited annotated samples. And we also introduce a 4-way tuple-contrast training strategy to positively activate the training progress of our object detector. Experiments over two few-shot benchmarks (Pascal VOC, MS-COCO) demonstrate that, our proposed CRTED without further fine-tuning can achieve comparable performance with current state-of-the-art fine-tuned works. The codes and pre-trained models will be released.

The development of computational acoustics allows simulation of sound generation and propagation in complex environment. In particular, meshfree methods are widely used to solve acoustics problems through arbitrarily distributed field points and approximation smoothness flexibility. As a Lagrangian meshfree method, smoothed particle hydrodynamics (SPH) method reduce the difficulty in solving problems with deformable boundaries, complex topologies, or multiphase medium. The traditional SPH method has been applied in acoustic simulation. This study presents the corrective smoothed particle method (CSPM), which is a combination of SPH kernel estimate and Taylor series expansion. The CSPM is introduced as a Lagrangian approach to improve accuracy in solving acoustic wave equations in the time domain. Moreover, a boundary treatment technique based on the hybrid meshfree and finite difference time domain (FDTD) method is proposed to represent different acoustic boundaries with particles. To model sound propagation in pipes with different boundaries, soft, rigid, and absorbing boundary conditions are built with this technique. Numerical results show that the CSPM algorithm is consistent and demonstrates convergence with exact solutions. Main computational parameters are discussed, and different boundary conditions are validated to be effective for benchmark problems in computational acoustics.

The eddy current loss should be optimized to be as less as possible for the stability of permanent magnet in high speed permanent magnet synchronous motor (HSPMSM) rotor and ensure the high efficiency and low temperature of the motor. This paper analyzes the eddy current distribution in rotor, with consideration of the conflict of the thickness of sleeve and diameter of the rotor, calculating the eddy current loss (ECL) and the thermal distribution via Separation of variables method for solving Maxwell's equations with analytical hieratical model of ECL constructed. The optimization result of ECL of the HSPMSM whose power and rated speed is 30kw 48000r/min can be got by multi-objective optimization method, combined weighting coefficient method and traversal algorithm based on chaotic local search particle swarm optimization (CLSPSO), utilizing ECL analytical model and other analytical constraints. Related experiment and measurement has been implemented with new approach of loss separation.

Although several carbon sequestration methods have been proposed according to theories from various disciplines, it is not known which method is the best. This study evaluated and summarized the advantage and disadvantages of several major carbon sequestration methods, including carbon capture and sequestration, ocean alkalinization, algal cultivation, and wood burial, based on the first principles, namely, sequestration scale and time, elemental stoichiometry, and energy use efficiency. This study suggested that, at present, wood burial may be a leading candidate for carbon sequestration because it can be implemented immediately on a large scale, is cost-effective and efficient, has a long sequestration time, has low technical requirements, and has a relatively low impact on agriculture. This study also discussed the implementation of wood burial from the perspective of nutrient requirements. To achieve carbon neutrality by 2050, the present study proposed a 25-year project starting in 2025 with an average sequestration rate of 3 Pg C per year, which includes burying 1.5 Pg of dead wood carbon and the creation of 9.7 × 10⁶ ha woodland.

This paper aims at tackling with the task of fusion feature from images and its corresponding point clouds for 3D object detection in autonomous driving scenarios basing on AVOD, an Aggregate View Object Detection network. The proposed fusion algorithms fuse features targeted from Bird’s Eye View (BEV) LIDAR point clouds and its corresponding RGB images. Differs in existing fusion methods, which are simply the adoptions of concatenation module, element-wise sum module or element-wise mean module, our proposed fusion algorithms enhance the interaction between BEV feature maps and its corresponding images feature maps by designing a novel structure, where single level feature maps and another utilizes multilevel feature maps. Experiments show that our proposed fusion algorithm produces better results on 3D mAP and AHS with less speed loss comparing to existing fusion method used on the KITTI 3D object detection benchmark.

In offshore drilling, accidents such as gas invasion, overflow, and kicks are inevitable, and they can escalate into blowouts and other catastrophic events that result in casualties and substantial economic losses. Therefore, maintaining drilling safety requires accurate monitoring of gas invasion and overflow. The majority of overflow monitoring methods currently utilized at drilling sites are threshold-based. However, monitoring parameters acquired during actual drilling operations frequently contain noise signals, making it difficult for threshold-based methods to strike a balance between improving accuracy and minimizing false positives. In this paper, Pattern Recognition-based Kick Detection (PRKD) is proposed as a novel method for diagnosing overflow in offshore drilling. This method utilizes the overflow evolution process by integrating multi-phase flow calculations, data filtering theory, pattern recognition theory, the Bayesian framework, and other theoretical models. The PRKD effectively detects and monitors gas intrusion and overflow based on single parameters by analyzing the shape and wave characteristics of the curves. The case analysis demonstrates that the proposed method for monitoring drilling overflow achieves high precision while maintaining a low false positive rate. By combining advanced computational techniques with pattern recognition algorithms, the PRKD improves the accuracy and reliability of kick detection, enabling proactive responses to potential risks, protecting the environment and human lives, and optimizing drilling operations.

Wideband signal detection is an important problem in wireless communication. With the rapid development of deep learning (DL) technology, some DL-based methods are applied to wireless technology, and the effect is obvious. In this paper, we propose a novel neural network for multi-type signal detection that can locate signals and recognize signal types in wideband spectrogram. Our network utilizes the key point estimation to locate the rough centerline of signal region and identify class. Then, several regressions are carried out to achieve properties, such as local offset and border offsets of bounding box, which is further synthesized for a more fine location. Experimental results demonstrate that our method performs more accurate than other DL-based object detection methods previously employed for the same detection task. Specifically, our method runs obviously faster than existing methods, and abandons the anchor generation, which makes it more favorable for real-time applications.

With the fast development of the mobile Internet, the online platforms of social networks have rapidly been developing for the purpose of making friends, sharing information, etc. In these online platforms, users being related to each other forms social networks. Literature reviews have shown that social networks have community structure. Through the studies of community structure, the characteristics and functions of networks structure and the dynamical evolution mechanism of networks can be used for predicting user behaviours and controlling information dissemination. Therefore, this study proposes a deep community detection method which includes (1) matrix reconstruction method, (2) spatial feature extraction method and (3) community detection method. The original adjacency matrix in social network is reconstructed based on the opinion leader and nearer neighbors for obtaining spatial proximity matrix. The spatial eigenvector of reconstructed adjacency matrix can be extracted by an auto-encoder based on convolution neural network for the improvement of modularity. In experiments, four open datasets of practical social networks were selected to evaluate the proposed method, and the experimental results show that the proposed deep community detection method obtained higher modularity than other methods. Therefore, the proposed deep community detection method can effectively detect high quality communities in social networks.

This study proposes a mobile positioning method which adopts recurrent neural network algorithms to analyze the received signal strength indications from heterogeneous networks (e.g., cellular networks and Wi-Fi networks) for estimating the locations of mobile statioThis study proposes a mobile positioning method which adopts recurrent neural network algorithms to analyze the received signal strength indications from heterogeneous networks (e.g., cellular networks and Wi-Fi networks) for estimating the locations of mobile stations. The recurrent neural networks with multiple consecutive timestamps can be applied to extract the features of time series data for the improvement of location estimation. In practical experimental environments, there are 4,525 records, 59 different base stations, and 582 different Wi-Fi access points detected in Fuzhou University in China. The lower location errors can be obtained by the recurrent neural networks with multiple consecutive timestamps (e.g., 2 timestamps and 3 timestamps); the experimental results can be observed that the average error of location estimation was 9.19 meters by the proposed mobile positioning method with 2 timestamps.

Despite the expectation that social media use in the public sector contributes to enhancing government's transparency, few studies have been investigated whether social media use actually leads to more disclosure during environmental incidents in practice and how social media influence local governments and their officials' information disclosure. In this article, we model information disclosure during environmental incidents as an evolutionary game process between the central government and local government in social media context, and examine the internal mechanism that how social media influence the progress of information disclosure during environmental incidents. The findings indicate that social media plays an active constructive role in central-local government game relations. Specific- ally, social media can provides an efficient information channels for the central government supervise regional officials in environmental incidents, and thus improves its supervision efficiency, and it also provides an important means for internet mobilization and online-offline interaction by encouraging the public exchange information and express their views, and in turn forces local governments and their officials tend to disclosure ahead.

The massive use of electronic equipment has raised concerns about electromagnetic (EM) pollution, leading to increased attention to EM shielding in both civil and military applications. EM absorption materials play a crucial role in reducing the energy of microwaves projected onto their surface. In this work, we propose a novel OTA (over-the-air) antenna test method to evaluate and analyze the functionality of EM absorption materials. This method offers a new and practical way to assess the effectiveness of these materials. Measured results indicate that the presence of the EM absorption material led to a decrease in antenna gain of approximately 2-3 dB, a reduction in efficiency of more than 10-15%, and a smaller radiation pattern during the actual testing process. These findings highlight the impact of EM absorption materials on antenna performance. Compared to the traditional S-parameter testing method, the gain comparison testing method exhibits the advantages of higher accuracy and simpler operation in the lower frequency experiment.

: This study focuses on optimizing chlorophyll extraction techniques and strategically placing leaf disks to enhance chlorophyll concentration in sesame (Sesamum indicum L.) leaves. Thirty sesame genotypes, categorized into light green (LG), middle green (MG), and deep green (DG) pigment groups based on leaf coloration, were selected from a larger pool of field-grown accessions. The investigation involved determining optimal SPAD value index measurements, quantifying pigment concentrations, exploring extraction solvents, and selecting suitable leaf disk positions. Significant variations in chlorophyll content were observed across genotypes, greenness categories, and leaf disk positions. The categorization of genotypes into DG, MG, and LG groups revealed a correlation between leaf appearance and chlorophyll content. The study highlighted a consistent relationship between carotenoids and chlorophyll, indicating their role in adaptation to warm environments. Examination of leaf disk positions revealed a significant chlorophyll gradient along the leaf blade, emphasizing the need for standardized protocols. Chlorophyll extraction experiments identified DMSO and 96% ethanol, particularly the later incubated for 10 minutes at 85°C, as effective choices. This recommendation considers factors like cost-effectiveness, time efficiency, safety, and environmental regulations, ensuring consistent and simplified extraction processes. For higher chlorophyll extraction, focusing on leaf tips and the 75% position along the sesame leaf blade is suggested, consistently yielding higher chlorophyll content. Our findings therefore, underscores insightful knowledge on chlorophyll gradients and encouraging for standardized protocols, that enabling researchers to refine experimental designs for precise and comparable chlorophyll measurements. Recommended solvent choices ensure reliable outcomes in plant physiology, ecology, and environmental studies.

In order to study the effects of irradiation on the physicochemical properties and digestion behavior of chickpea protein, chickpea protein concentrate (CPC) was treated with electron beam irradiation (EBI) at doses of 5, 10, 15 and 20 kGy, respectively. After irradiation, protein solubility first increased at 10 kGy and 15 kGy, and then decreased at higher dose of 20 kGy. This was supported by SDS-PAGE where the intensity of major protein bands first increased and then decreased. Increased does of EBI generally led to greater oxidative modification of proteins in CPC, indicated by reduced sulfhydryls and increased carbonyls. In addition, protein structure was modified by EBI shown by Fourier transform infrared spectroscopy analysis where α-helix generally decreased and β-sheet increased. Although the protein digestibility was not significantly affected by EBI, the peptidomic analysis of the digests revealed significant difference among CPC irradiated with varying doses. A total of 337 peptides were identified from CPC irradiated with 0 kGy, 10 kGy and 20 kGy, respectively, with 18 overlapping peptides and 60, 29 and 40 peptides specific to the groups of 0, 10 and 20 kGy respectively. Theoretical calculation showed that the distribution of peptide length, hydrophobicity, net charge, and C-terminal residues were affected by irradiation. The 2, 2'-azino-bis (3-ethylbenzothiazoline-6-sulfonic acid) (ABTS) radical scavenging activity showed a marginal decrease with increasing dose of irradiation. In conclusion, EBI led to oxidative modification and structural changes of the chickpea protein, which subsequently affected the physicochemical properties of peptides obtained from in-vitro digestion of CPC despite of similar digestibility.

Osteoarthritis (OA) has become one of the most common disabilities among elders, especially in female. Obesity and mechanical injury causing OA are attributed to joint loading, cartilage disintegration, bone loss and inflammation as well. Several strategies used for treatment OA including non-pharmacological and pharmacological. Fucoidan possesses several bioactivities such as antitumor, antiviral, anticoagulation, anti-obesity, and immunomodulation. This study aims to investigate the effect of fucoidan in surgery-induced OA on diet-induced obesity rats. OA was induced by anterior cruciate ligament transection and partial medial meniscectomy (ACLT+MMx). Male SD rats were fed high-fat diet (HFD) for 4 weeks to induce obesity before ACLT+MMx to induce OA. OA rats were administered with intragastric water or fucoidan in three different concentrations (32 mg/kg, 64 mg/kg, and 320 mg/kg) after the surgeries for 40 days with HFD. We observed that the swelling in knee joint was alleviated and hind paw weight distribution was rectified after feeding fucoidan, with no significant effect on weight gain and feed intake. Fucoidan administration indicated no significant variation on HDL-Cholesterol level, but reduced plasma triglycerides and LDL-Cholesterol level. In addition, weight-bearing tests showed improvement in the fucoidan-treated group. Our results suggested that fucoidan may improve meniscal/ligamentous injury and obesity-induced OA.

This paper presents a piezoresistive pressure sensor with a shield layer for improved stability. Compared with the conventional piezoresistive pressure sensors, p-type piezoresistors are covered by an n-type shield layer, which is formed by ion implantation. The proposed pressure sensors have been successfully fabricated by bulk micromachining techniques. The impact of electrical field on piezoresistors is studied by simulation. The temperature drift of the pressure sensor has been investigated by both simulation and experimental measurement. Characteristics of developed pressure sensors are tested from -40 C to 125 C. A sensitivity of 0.022 mV/V/KPa and a maximum non-linearity of 0.085% FS are measured for the fabricated sensor in a pressure range of 1 MPa. The temperature coefficients of resistance of shielded piezoresistors are found to be smaller than those of un-shielded ones. It is demonstrated that the shield layer is able to reduce the drift caused by electrical field and ambient temperature variation.

Celiac disease is an autoimmune disease triggered by oral ingestion of gluten, with certain gluten residues resistant to digestive tract enzymes. Within the duodenum, the remaining peptides incite immunogenic responses, including the generation of autoantibodies and inflammation, leading to irreversible damage. Our previous exploration unveiled a glutenase called Bga1903 derived from the Gram-negative bacterium Burkholderia gladioli. The cleavage pattern of Bga1903 indicated its moderate ability to mitigate the toxicity of pro-immunogenic peptides. The crystal structure of Bga1903, along with the identification of subsites within its active site, was determined. To improve its substrate specificity toward prevalent motifs like QPQ within gluten peptides, the active site of Bga1903 underwent site-directed mutagenesis according to structural insights and enzymatic kinetics. Among the double-site mutants, E380Q/S387L exhibits an approximately 38-fold increase in its specificity constant toward the QPQ sequence, favoring glutamines at the P1 and P3 positions compared to the wild type. Not only does the heightened specificity of E380Q/S387L improve the hydrolytic activity against pro-immunogenic peptides, but also holds this version of the enzyme as a promising candidate as an oral therapy enzyme for celiac disease.

The proportion of adults aged over 60 years in the world is expected to reach 20% by the year 2050. Ageing is associated with several physiological changes that increase the risk of malnutrition among this population. Malnutrition is characterized by deficiencies or insufficiencies of macro- and micronutrients. Malnutrition has detrimental effects on the health, wellbeing and quality of life of older adults. Nuts are rich in energy, unsaturated fats, protein, as well as other nutrients that provide a range of health benefits. While the effects of nuts on overnutrition have been studied extensively, very few studies have been specifically designed to understand the role of nuts in mitigating undernutrition in the elderly. Therefore, this review explores the potential role of nuts in improving the nutritional status of older adults who are at risk of undernutrition. Several properties of whole nuts, some of which appear important for addressing overnutrition, (e.g. hardness, lower-than-expected nutrient availability, satiety-enhancing effects) may limit their effectiveness as a food to combat undernutrition. However, we propose that modifications such as transforming the physical form of nuts, addressing the timing of nut ingestion, and introducing variety may overcome these barriers. This review also discusses the feasibility of using nuts to prevent and reverse undernutrition among older adults. We conclude with a recommendation to conduct clinical studies in the future to test this conceptual framework.

In this paper, the distributed formation tracking control problem of quadrotor unmanned aerial vehicles (UAVs) is considered. Adaptive backstepping technology is used to design flight control schemes for quadrotor UAVs. For the position subsystem, a distributed robust formation tracking control scheme is developed to achieve formation flight of quadrotor UAVs and track the desired flight trajectory. For the attitude subsystem, an adaptive disturbance rejection control scheme is proposed to achieve attitude stabilization during UAV flight under uncertain disturbances. Compared with the existing results, the novelty of this paper is that the proposed formation control scheme does not require the use of the quadrotor model parameters. Finally, a quadrotor UAV swarm system is used to verify the effectiveness of the proposed control scheme.

Numerous dynamic and complicated processes characterize development from the oocyte to the embryo. However, given the importance of functional transcriptome profiles, long non-coding RNAs, single-nucleotide polymorphisms, and alternative splicing during embryonic development, the effect that these features have on the blastomeres of 2-, 4-, 8-, 16-cell, and morula stages of development have not been studied. Here, we conducted a scRNA-seq survey of cells from sheep from the oocyte to the blastocyst developmental stages. We then carried out experiments to identify and functionally analyze the transcriptome profiles, long non-coding RNAs, single-nucleotide polymorphisms (SNPs), and alternative splicing (AS). We founded that between the oocyte and zygote groups significantly down-regulated genes and the second-largest change in gene expression occurred between the 8- and 16-cell stages. We used various methods to construct a profile to characterize cellular and molecular features and systematically analyze the related GO and KEGG profile of cells of all stages from the oocyte to the blastocyst. This large-scale, single-cell atlas provides key cellular information and will likely assist clinical studies in improving preimplantation genetic diagnosis.

In recent years, due to their frequent use and widespread use, IoT (Internet of Things) devices have become an attractive target for hackers. As a result of their limited network resources and complex operating systems, they are vulnerable to attacks. Using a honeypot can, therefore, be a very effective way of detecting malicious requests and capturing samples of exploits. The purpose of this article is to introduce honeypots, the rise of IoT devices, and how they can be exploited by attackers. Various honeypot ecosystems will be investigated further for capturing and analyzing information from attacks against these IoT devices. As well as how to leverage proactive strategies in terms of IoT security, it will provide insights on the attack vectors present in most IoT systems, along with understanding attack patterns.

Precision agriculture (PA) is a holistic, sustainable, innovative systems approach that assists farmers in production management. Adopting PA could improve sustainable food security and community economic sustainability. Developing an understanding of PA adoption attributes is needed to assist extension practitioners to promote adoption and better understand the innovation adoption phenomena. A systematic review of literature was conducted to investigate PA adoption. Thirty-three publications were examined, and four themes were found among the reviewed publications. The results were interpreted using Rogers’ diffusion of innovations framework to address the research objectives. Of the reviewed literature, we found relative advantage and compatibility were two dominant attributes to strengthen the adoption of PA, and the complexity attribute was rarely used to promote the adoption of PA. This study shows that change agents do not fully use five attributes of innovation when they promote PA technology to stakeholders to adopt. Thus, we recommend studies from the agricultural extension specialists’ perspectives in the future may determine contributions to motivate farmers’ adoption of PA, in particular related to complexity.