Defect annihilation of the IGZO/SiO₂ layer is of great importance to enhancing the bias stress stabilities of bottom-gate coplanar thin-film transistors (TFTs). The effects of annealing temperatures (T_a) on the structure of the IGZO/SiO₂ layer and the stabilities of coplanar IGZO TFTs were investigated in this work. An atomic depth profile showed that the IGZO/SiO₂ layer included an IGZO layer, an IGZO/SiO₂ interfacial mixing layer, and a SiO₂ layer. Higher T_a had only one effect on the IGZO layer and SiO₂ layer (i.e., strengthening chemical bonds), while it had complex effects on the interfacial mixing layer—including weakening M-O bonds (M: metallic elements in IGZO), strengthening damaged Si-O bonds, and increasing O-related defects (e.g., H₂O). At higher T_a, IGZO TFTs exhibited enhanced positive bias temperature stress (PBTS) stabilities but decreased negative bias temperature stress (NBTS) stabilities. The enhanced PBTS stabilities were correlated with decreased electron traps due to the stronger Si-O bonds near the interfacial layer. The decreased NBTS stabilities were related to increased electron de-trapping from donor-like defects (e.g., weak M-O bonds and H₂O) in the interfacial layer. Our results suggest that although higher T_a annihilated the structural damage at the interface from ion bombardment, it introduced undesirable defects. Therefore, to comprehensively improve electrical stabilities, controlling defect generation (e.g., by using a mild sputtering condition of source/drain electrodes and oxides) was more important than enhancing defect annihilation (e.g., through increasing T_a). Full article

Plasmodium vivax (Pv) accounts for over 50% of malaria cases in Latin America and Asia. Despite a significant reduction in Pv transmission in Thailand, the parasite remains endemic to the border areas. This study aimed to investigate the genetic diversity of the parasites and the host factors, as well as their relation to parasite density in Pvisolates, along the Thai–Myanmar border. Genetic variations in Pv markers, specifically the ookinete surface protein Pvs25, and host genes, including Toll-like receptor 6 (TLR6), TLR9, TIR Domain-containing adaptor protein (TIRAP), Toll-interacting protein (TOLLIP), Duffy antigen receptor for chemokines (DARC), and intercellular adhesion molecule 1 (ICAM-1), were investigated using polymerase chain reaction (PCR) with restriction fragment length polymorphism (RFLP). A total of 548 PCR-positive Pv samples collected from Tak and Kanchanaburi provinces during two periods (2006–2007 and 2014–2016) were included in the study. Pvs25 exhibited four haplotypes, with H1 (EGTKV) being the most prevalent in both provinces. Kanchanaburi isolates exhibited greater genetic diversity than Tak isolates. No significant deviations from neutrality were observed for Pvs25 in either area. ICAM-1 and TOLLIP s3750920 heterozygous carriers had greater median parasite densities than homozygous mutants. The TLR9 rs187084 T genotype had a significantly higher parasite density than the non-T genotype. The findings underscore the significant association between the rs3750920 C/T, rs5498 A/G, and rs187084 T genotypes and high parasite density in patients infected with Pv, highlighting their potentially critical role in malaria susceptibility. Full article

The submerged floating tunnel (SFT) is a novel form of transportation infrastructure for crossing deeper and wider seas. One of the primary challenges in designing SFTs is understanding their hydrodynamic response to complex environmental loads. In order to investigate the two-degree-of-freedom (2-DOF) flow-induced vibration (FIV) response of SFTs under current, a two-dimensional (2D) numerical model was developed using the Reynolds-averaged Navier–Stokes (RANS) method combined with the fourth-order Runge–Kutta method. The numerical results were validated by comparing them with the existing literature. The study then addressed the effects of coupled vibration and structural parameters, i.e., the mass ratio and natural frequency ratio, on the response and wake pattern of SFTs, numerically. The results indicated that coupled vibration had a significant impact on the SFT response at reduced velocities of Ur_wx ≥ 4.4. A decrease in mass ratio (m* < 1) notably amplified the 2-DOF vibration amplitudes of SFTs at Ur_wx ≥ 4.4, particularly for in-line vibration. Similarly, a decrease in natural frequency ratio (R_f < 1) significantly suppressed the in-line vibration of SFTs at Ur_wx ≥ 2.5. Therefore, for the design of SFTs, careful consideration should be given to the effect of mass ratio and natural frequency ratio on in-line vibration. Full article

The process of adipocyte browning has recently emerged as a novel therapeutic target for combating obesity and obesity-related diseases. Non-shivering thermogenesis is the process of biological heat production in mammals and is primarily mediated via brown adipose tissue (BAT). The recruitment and activation of BAT can be induced through chemical drugs and nutrients, with subsequent beneficial health effects through the utilization of carbohydrates and fats to generate heat to maintain body temperature. However, since potent drugs may show adverse side effects, nutritional or natural substances could be safe and effective as potential adipocyte browning agents. This review aims to provide an extensive overview of the natural food compounds that have been shown to activate brown adipocytes in humans, animals, and in cultured cells. In addition, some key genetic and molecular targets and the mechanisms of action of these natural compounds reported to have therapeutic potential to combat obesity are discussed. Full article

Based on the hourly surface ozone (O₃) observations and meteorological data from Zhuzhou in 2021, the pollution characteristics and influencing factors of O₃ in Zhuzhou were investigated in the study. In addition, the Potential Source Contribution Function (PSCF) and Concentration Weighted Trajectory (CWT) analysis methods were employed to analyze the transmission paths and potential pollution sources of O₃ pollution in Zhuzhou. The results showed that the total number of days with O₃ exceeding the standard at all monitoring stations in Zhuzhou was 142 days in 2021. The overall air quality was less affected by SO₂, NO₂, and CO, and the trend of O₃ pollution was still increasing. The concentrations of O₃, CO, and NO₂ varied significantly in different months, and the variation of O₃ exhibited a “double-peak” pattern, with the peak value occurring in September. The O₃ concentration in urban areas was significantly higher than that in suburban areas. Meteorological conditions had a significant impact on the degree of O₃ pollution in Zhuzhou. The average wind speed in Zhuzhou throughout the year was 1.7 m/s, and the prevailing wind direction in summer was southeast, with a frequency of 16%. O₃ pollution was mainly transported by short-distance airflow during the over-standard periods in 2021, accounting for 37.64%. The main source of O₃ pollutant was from Jiangxi Province in the east, with the shortest distance of regional transport and the highest O₃ concentration. In addition, transportation from central Guangdong Province, western Jiangxi Province, and central Hubei Province also had a significant impact. Full article

Traffic state classification and relevance calculation at intersections are both difficult problems in traffic control. In this paper, we propose an intersection relevance model based on a temporal graph attention network, which can solve the above two problems at the same time. First, the intersection features and interaction time of the intersections are regarded as input quantities together with the initial labels of the traffic data. Then, they are inputted into the temporal graph attention (TGAT) model to obtain the classification accuracy of the target intersections in four states—free, stable, slow moving, and congested—and the obtained neighbouring intersection weights are used as the correlation between the intersections. Finally, it is validated by VISSIM simulation experiments. In terms of classification accuracy, the TGAT model has a higher classification accuracy than the three traditional classification models and can cope well with the uneven distribution of the number of samples. The information gain algorithm from the information entropy theory was used to derive the average delay as the most influential factor on intersection status. The correlation from the TGAT model positively correlates with traffic flow, making it interpretable. Using this correlation to control the division of subareas improves the road network’s operational efficiency more than the traditional correlation model does. This demonstrates the effectiveness of the TGAT model’s correlation. Full article

This study aims to develop multi-functional bio-safe dental resin composites with capabilities for mineralization, high in vitro biocompatibility, and anti-biofilm properties. To address this issue, experimental resin composites consisting of UDMA/TEGDMA-based dental resins and low quantities (1.9, 3.8, and 7.7 vol%) of 45S5 bioactive glass (BAG) particles were developed. To evaluate cellular responses of resin composites, MC3T3-E1 cells were (1) exposed to the original composites extracts, (2) cultured directly on the freshly cured resin composites, or (3) cultured on preconditioned composites that have been soaked in deionized water (DI water), a cell culture medium (MEM), or a simple HEPES-containing artificial remineralization promotion (SHARP) solution for 14 days. Cell adhesion, cell viability, and cell differentiation were, respectively, assessed. In addition, the anti-biofilm properties of BAG-loaded resin composites regarding bacterial viability, biofilm thickness, and biofilm morphology, were assessed for the first time. In vitro biological results demonstrated that cell metabolic activity and ALP expression were significantly diminished when subjected to composite extracts or direct contact with the resin composites containing BAG fillers. However, after the preconditioning treatments in MEM and SHARP solutions, the biomimetic calcium phosphate minerals on 7.7 vol% BAG-loaded composites revealed unimpaired or even better cellular processes, including cell adhesion, cell proliferation, and early cell differentiation. Furthermore, resin composites with 1.9, 3.8, and 7.7 vol% BAG could not only reduce cell viability in S. mutans biofilm on the composite surface but also reduce the biofilm thickness and bacterial aggregations. This phenomenon was more evident in BAG7.7 due to the high ionic osmotic pressure and alkaline microenvironment caused by BAG dissolution. This study concludes that multi-functional bio-safe resin composites with mineralization and anti-biofilm properties can be achieved by adding low quantities of BAG into the resin system, which offers promising abilities to mineralize as well as prevent caries without sacrificing biological activity. Full article

It has been observed that the leaves of some Zamia species undergo a kind of “reverse ripening”; that is, they change from their original brown color to green during development. We assumed that this strange color change was due to the change in carotenoid composition, so we followed the changes for several weeks. The detailed carotenoid composition and content at different stages of development of the leaves was determined with HPLC-DAD focusing on the changes in red and yellow carotenoids. The total and relative amounts of red and yellow carotenoids were determined simultaneously from one measurement from a saponified and/or unsaponified extract. At the beginning of development, the concentration of red carotenoids was higher than that of the yellow ones; it decreased drastically until 22 days and continued to decrease slowly until they completely disappeared. The concentration of yellow carotenoids decreased at the beginning as well, but after 22 days it started to increase. The amount of red carotenoids started to decrease when the leaflet stopped growing. Lutein is the main component in old leaflets, which is not a red carotenoid precursor. Red carotenoids can always be found in their esterified form in the leaves. These findings support the hypothesis that red and yellow carotenoid accumulation are independent and probably have different functions in the leaflet. The strange color change was explained based on the compartmentalization of red and yellow carotenoids and on the changing activity of the enzyme capsanthin–capsorubin synthase responsible for the synthesis of red carotenoids capsorubin and capsanthin. Full article

The dimensional accuracy and microstructure affect the service performance of parts fabricated by wire arc additive manufacturing (WAAM). Regulating the geometry and microstructure of such parts presents a challenge. The coupling method of an artificial neural network and finite element (FE) is proposed in this research for this purpose. Back-propagating neural networks (BPNN) based on optimization algorithms were established to predict the bead width (BW) and height (BH) of the deposited layers. Then, the bead geometry was modeled based on the predicted dimension, and 3D FE heat transfer simulation was performed to investigate the evolution of temperature and microstructure. The results showed that the errors in BW and BH were less than 6%, and the beetle antenna search BPNN model had the highest prediction accuracy compared to the other models. The simulated melt pool error was less than 5% with the experimental results. The decrease in the ratio of the temperature gradient and solidification rate induced the transition of solidified grains from cellular crystals to columnar dendrites and then to equiaxed dendrites. Accelerating the cooling rate increased the primary dendrite arm spacing and δ-ferrite content. These results indicate that the coupling model provides a pathway for regulating the dimensions and microstructures of manufactured parts. Full article

Scrap steel represents a sustainable and recyclable resource, instrumental in diminishing carbon footprints and facilitating the eco-friendly evolution of the steel sector. However, current scrap steel recycling faces a series of challenges, such as high labor intensity and occupational risks for inspectors, complex and diverse sources of scrap steel, varying types of materials, and difficulties in quantifying and standardizing manual visual inspection and rating. Specifically, we propose WaveSegNet, which is based on wavelet transform and a multiscale focusing structure for scrap steel segmentation. Firstly, we utilize wavelet transform to process images and extract features at different frequencies to capture details and structural information in the images. Secondly, we introduce a mechanism of multiscale focusing to further enhance the accuracy of segmentation by extracting and perceiving features at different scales. Through experiments conducted on the public Cityscapes dataset and scrap steel datasets, we have found that WaveSegNet consistently demonstrates superior performance, achieving the highest scores on the mIoU metric. Particularly notable is its performance on the real-world scrap steel dataset, where it outperforms other segmentation algorithms with an average increase of 3.98% in mIoU(SS), reaching 69.8%, and a significant boost of nearly 5.98% in mIoU(MS), achieving 74.8%. These results underscore WaveSegNet’s exceptional capabilities in processing scrap steel images. Additionally, on the publicly available Cityscapes dataset, WaveSegNet shows notable performance enhancements compared with the next best model, Segformer. Moreover, with its modest parameters and computational demands (34.1 M and 322 GFLOPs), WaveSegNet proves to be an ideal choice for resource-constrained environments, demonstrating high computational efficiency and broad applicability. These experimental results attest to the immense potential of WaveSegNet in intelligent scrap steel rating and provide a new solution for the scrap steel recycling industry. These experimental results attest to the immense potential of WaveSegNet in intelligent scrap steel rating and provide a new solution for the scrap steel recycling industry. Full article

Enterohemorrhagic Escherichia coli (EHEC) is a critical public health concern due to its role in severe gastrointestinal illnesses in humans, including hemorrhagic colitis and the life-threatening hemolytic uremic syndrome. While highly pathogenic to humans, cattle, the main reservoir for EHEC, often remain asymptomatic carriers, complicating efforts to control its spread. Our study introduces a novel method to investigate EHEC using organoid-derived monolayers from adult bovine ileum and rectum. These polarized epithelial monolayers were exposed to EHEC for four hours, allowing us to perform comparative analyses between the ileal and rectal tissues. Our findings mirrored in vivo observations, showing a higher colonization rate in the rectum compared with the ileum (44.0% vs. 16.5%, p < 0.05). Both tissues exhibited an inflammatory response with increased expression levels of TNF-a (p < 0.05) and a more pronounced increase of IL-8 in the rectum (p < 0.01). Additionally, the impact of EHEC on the mucus barrier varied across these gastrointestinal regions. Innovative visualization techniques helped us study the ultrastructure of mucus, revealing a net-like mucin glycoprotein organization. While further cellular differentiation could enhance model accuracy, our research significantly deepens understanding of EHEC pathogenesis in cattle and informs strategies for the preventative measures and therapeutic interventions. Full article

In this narrative, comprehensive, and updated review of the literature, we summarize evidence about the effectiveness of interventions aimed at reducing emotion dysregulation and improving emotion regulation in children, adolescents, and adults. After introducing emotion dysregulation and emotion regulation from a theoretical standpoint, we discuss the factors commonly associated with emotion regulation, including neurobiological and neuropsychological mechanisms, and the role of childhood adverse experiences and psycho–social factors in the onset of emotion dysregulation. We then present evidence about pharmacological and non-pharmacological interventions aiming at improving emotion dysregulation and promoting emotion regulation across the lifespan. Although our review was not intended as a traditional systematic review, and the search was only restricted to systematic reviews and meta-analyses, we highlighted important implications and provided recommendations for clinical practice and future research in this field. Full article

Pests in pastures have compromised the production of biomass for feeding livestock herds. Many strategies have been applied to sustainably solve this problem. One viable and innovative technique is the delivery of entomopathogenic fungi through endophytes. Therefore, this study aimed to (i) evaluate the endophytic capacity of two entomopathogenic fungi, Fusarium multiceps UFMGCB 11443 and Metarhizium anisopliae UFMGCB 11444, in Urochloa brizantha [(Hochst. ex A. Rich.) Stapf] (Poaceae) cultivar ‘Marundu’) via foliar inoculation or seed treatment, and (ii) measure their efficiency in controlling Mahanarva spectabilis Distant, 1909 (Hemiptera: Cercopidae) in U. brizantha. In the greenhouse, the fungi colonized the tissues of U. brizantha plants when inoculated via foliar spraying or seed treatment. The fungi F. multiceps and M. anisopliae caused 88% and 97.1% epizootic effects via seed inoculation, respectively, and 100% epizootic effects via foliar inoculation. In the field, the lowest fungal dose of 0.5 kg/ha had the same effect as a fourfold greater dose, with a >86% decrease in insect pest infestation observed. In summary, the fungi F. multiceps and M. anisopliae have endophytic effects and can effectively control M. spectabilis in U. brizantha pastures. Full article

Using information-theoretic quantities in practical applications with continuous data is often hindered by the fact that probability density functions need to be estimated in higher dimensions, which can become unreliable or even computationally unfeasible. To make these useful quantities more accessible, alternative approaches such as binned frequencies using histograms and k-nearest neighbors (k-NN) have been proposed. However, a systematic comparison of the applicability of these methods has been lacking. We wish to fill this gap by comparing kernel-density-based estimation (KDE) with these two alternatives in carefully designed synthetic test cases. Specifically, we wish to estimate the information-theoretic quantities: entropy, Kullback–Leibler divergence, and mutual information, from sample data. As a reference, the results are compared to closed-form solutions or numerical integrals. We generate samples from distributions of various shapes in dimensions ranging from one to ten. We evaluate the estimators’ performance as a function of sample size, distribution characteristics, and chosen hyperparameters. We further compare the required computation time and specific implementation challenges. Notably, k-NN estimation tends to outperform other methods, considering algorithmic implementation, computational efficiency, and estimation accuracy, especially with sufficient data. This study provides valuable insights into the strengths and limitations of the different estimation methods for information-theoretic quantities. It also highlights the significance of considering the characteristics of the data, as well as the targeted information-theoretic quantity when selecting an appropriate estimation technique. These findings will assist scientists and practitioners in choosing the most suitable method, considering their specific application and available data. We have collected the compared estimation methods in a ready-to-use open-source Python 3 toolbox and, thereby, hope to promote the use of information-theoretic quantities by researchers and practitioners to evaluate the information in data and models in various disciplines. Full article

The rail vehicle industry wants to produce vehicles with higher speeds, to maintain and increase its market share. However, when the speed of the vehicle increases, it may have an undesirable effect on ride comfort, in terms of ride dynamics. Recent developments towards lighter and faster vehicles make the problem of ride comfort at higher speeds increasingly important. Focusing on the behavior of flexible rather than rigid body behavior should not be neglected when designing long and light car bodies. There are several approaches to incorporate body flexibility in multibody simulations and they have some superiorities and weaknesses. In this study, an efficient and accurate vertical dynamic model for the ride comfort analysis is developed and implemented in a commercial object-oriented modeling (OOM) software Dymola (2015 FD01) which uses the open-source code Modelica. This model includes car body flexibility with the assembling of a rigid body approach. The developed model is compared to a three-dimensional vehicle model in the commercial Vampire software (Pro V5.50) at different velocities. For the vertical ride comfort analysis, the ISO 2631-1 standard was used for both the developed model and the three-dimensional model. The results are presented as acceleration history and $a^{wrms}$—weighted r.m.s (root mean square) of accelerations—as required by the standard. The developed model has shown its feasibility in terms of its efficiency and accuracy for the vertical ride comfort analysis. The accuracy of the model is evidenced by the fact that the car body vibration level at high speeds shows minor differences compared to the results of the Vampire, which is a validated commercial software in the area of rail vehicle dynamics. The approach involving the assembly of rigid bodies is applied for the first time for high-speed trains in dynamical modelling, with flexible car bodies for ride comfort analysis. Furthermore, it can be used for parametrical studies focusing on ride comfort, thereby offering a quite beneficial framework for addressing the challenges of ride comfort analysis in high-speed rail vehicles. Improvements for and analyses of other aspects are also possible, since the optimization and other useful libraries are readily available in Dymola/Modelica. Full article

Tethered balloon systems encounter various complex wind field environments during flight. To investigate the conditions under which the system can operate safely and smoothly, a longitudinal dynamic model for tethered balloon systems is established. The model incorporates a streamlined balloon shape with its aerodynamic center at the body’s center. Steady-state aerodynamic force coefficients are calculated through simulations and fitted to a function based on the angle of attack within a specified range. The complex cable model is simplified using the lumped mass method, considering the influence of branch cables on the main node position. Experimental results from windless oscillation tests on scaled tethered balloon systems are compared with numerical solutions obtained using the dynamic model under the same conditions, validating the feasibility of the model for simulating different wind field scenarios. Finally, the motion characteristics of tethered balloon systems in different wind fields are analyzed. The numerical simulation results show that in a horizontal step wind field, the cable tension and cable inclination angle increase with the wind speed, and the slower the wind field changes, the shorter the time required for system stabilization. Updrafts greatly increase the likelihood of balloon escape, while downdrafts greatly increase the likelihood of the system making contact with the ground. The findings of this study can provide a basis for selecting suitable wind field conditions and issuing risk warnings for tethered balloon systems. Full article

Chronic kidney disease poses a growing global health concern, as an increasing number of patients progress to end-stage kidney disease requiring kidney replacement therapy, presenting various challenges including shortage of care givers and cost-related issues. In this narrative essay, we explore innovative strategies based on in-depth literature analysis that may help healthcare systems face these challenges, with a focus on digital health technologies (DHTs), to enhance removal and ensure better control of broader spectrum of uremic toxins, to optimize resources, improve care and outcomes, and empower patients. Therefore, alternative strategies, such as self-care dialysis, home-based dialysis with the support of teledialysis, need to be developed. Managing ESKD requires an improvement in patient management, emphasizing patient education, caregiver knowledge, and robust digital support systems. The solution involves leveraging DHTs to automate HD, implement automated algorithm-driven controlled HD, remotely monitor patients, provide health education, and enable caregivers with data-driven decision-making. These technologies, including artificial intelligence, aim to enhance care quality, reduce practice variations, and improve treatment outcomes whilst supporting personalized kidney replacement therapy. This narrative essay offers an update on currently available digital health technologies used in the management of HD patients and envisions future technologies that, through digital solutions, potentially empower patients and will more effectively support their HD treatments. Full article

Carbon nanotubes (CNTs) are well known for their outstanding field emission (FE) performance, facilitated by their unique combination of electrical, mechanical, and thermal properties. However, if the substrate of choice is a poor conductor, the electron supply towards the CNTs can be limited, restricting the FE current. Furthermore, ineffective heat dissipation can lead to emitter–substrate bond degradation, shortening the field emitters’ lifetime. Herein, temperature-stable titanium nitride (TiN) was deposited by plasma-enhanced atomic layer deposition (PEALD) on different substrate types prior to the CNT growth. A turn-on field reduction of up to 59% was found for the emitters that were generated on TiN-coated bulk substrates instead of on pristine ones. This observation was attributed exclusively to the TiN layer as no significant change in the emitter morphology could be identified. The fabrication route and, consequently, improved FE properties were transferred from bulk substrates to free-standing, electrically insulating nanomembranes. Moreover, 3D-printed, polymeric microstructures were overcoated by atomic layer deposition (ALD) employing its high conformality. The results of our approach by combining ALD with CNT growth could assist the future fabrication of highly efficient field emitters on 3D scaffold structures regardless of the substrate material. Full article

With the progressive development of new energy technologies, high-power lithium batteries have been widely used in ship power systems due to their high-power density and low environmental pollution, and they have gradually become one of their main propulsion energy sources. However, the large-scale deployment of lithium batteries has also brought a series of safety problems to ship operations, especially the battery internal short circuit (ISC). Battery ISC faults are very hidden and unpredictable at the initial stage and often fail to be detected in time, ultimately leading to overheating, fire or even an explosion of the ship’s power system. Based on this, this paper proposes a fast and accurate method for early-stage ISC fault location and detection of lithium batteries. Initially, voltage variations across the lithium battery packs are quantified using curvilinear Manhattan distances to pinpoint faulty battery units. Subsequently, the localized characteristics of voltage variance among adjacent batteries are leveraged to detect an early-stage ISC fault. Simulation results indicate that the proposed method can quickly and accurately locate the position of 5 $\Omega$, 10 $\Omega$ and 15 $\Omega$ ISC faulty batteries within the battery pack, as well as detect the abnormal batteries in a timely manner with considerable sensitivity and reliability. Full article

Spatiotemporal information on individual trajectories in urban rail transit is important for operational strategy adjustment, personalized recommendation, and emergency command decision-making. However, due to the lack of journey observations, it is difficult to accurately infer unknown information from trajectories based only on AFC and AVL data. To address the problem, this paper proposes a spatiotemporal probabilistic graphical model based on adaptive expectation maximization attention (STPGM-AEMA) to achieve the reconstruction of individual trajectories. The approach consists of three steps: first, the potential train alternative set and the egress time alternative set of individuals are obtained through data mining and combinatorial enumeration. Then, global and local potential variables are introduced to construct a spatiotemporal probabilistic graphical model, provide the inference process for unknown events, and state information about individual trajectories. Further, considering the effect of missing data, an attention mechanism-enhanced expectation-maximization algorithm is proposed to achieve maximum likelihood estimation of individual trajectories. Finally, typical datasets of origin-destination pairs and actual individual trajectory tracking data are used to validate the effectiveness of the proposed method. The results show that the STPGM-AEMA method is more than 95% accurate in recovering missing information in the observed data, which is at least 15% more accurate than the traditional methods (i.e., PTAM-MLE and MPTAM-EM). Full article

Zero-shot event detection aims to involve the automatic discovery and classification of new events within unstructured text. Current zero-shot event detection methods have not considered addressing the problem more effectively from the perspective of improving event representations. In this paper, we propose dual-contrastive prompting (COPE) model for learning event representations to address zero-shot event detection, which leverages prompts to assist in generating event embeddings using a pretrained language model, and employs a contrastive fusion approach to capture complex interaction information between trigger representations and sentence embeddings to obtain enhanced event representations. Firstly, we introduce a sample generator to create ordered contrastive sample sequences with varying degrees of similarity for each event instance, aiding the model in better distinguishing different types of events. Secondly, we design two distinct prompts to obtain trigger representations and event sentence embeddings separately. Thirdly, we employ a contrastive fusion module, where trigger representations and event sentence embeddings interactively fuse in vector space to generate the final event representations. Experiments show that our model is more effective than the most advanced methods. Full article

Shale is composed of a rock matrix and bedding planes with a layered structure, resulting in significant anisotropy in its mechanical properties. In order to study the anisotropic mechanical properties of shale, the shale samples were prepared in different orientations with respect to the bedding planes, and the composition and microstructure of shale were first analyzed by X-ray diffractometer (XRD) and scanning electron microscope (SEM), and then the uniaxial and triaxial compression experiment on shale samples with five different bedding angles (the angle between the loading direction and the normal direction of the bedding planes, 0°, 30°, 45°, 60°, and 90°) were conducted under five confining pressures (0, 10, 20, 30, and 40 MPa), respectively; meanwhile, the acoustic emission (AE) test was carried out in the uniaxial test. The results indicate that the mechanical properties and parameters of shale have obvious anisotropy, and the AE characteristics of shale samples with different bedding angles are significantly different during uniaxial loading. Furthermore, the compressive strength and elastic modulus of the shale samples first decrease and then increase with the increase in the bedding angle under different confining pressures. Moreover, according to the anisotropic grade of compressive strength, the shale has moderate anisotropy. In addition, the failure mode of the shale samples is also anisotropic, and varies with the bedding angle and confining pressure. Full article