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Satellite sea surface temperature (SST) images are valuable for various oceanic applications, including climate monitoring, ocean modeling, and marine ecology. However, cloud cover often obscures SST signals, creating gaps in the data that reduce resolution and hinder spatiotemporal analysis, particularly in the waters
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Satellite sea surface temperature (SST) images are valuable for various oceanic applications, including climate monitoring, ocean modeling, and marine ecology. However, cloud cover often obscures SST signals, creating gaps in the data that reduce resolution and hinder spatiotemporal analysis, particularly in the waters near Taiwan. Thus, gap-filling methods are crucial for reconstructing missing SST values to provide continuous and consistent data. This study introduces a gap-filling approach using the Double U-Net, a deep neural network model, pretrained on a diverse dataset of Level-4 SST images. These gap-free products are generated by blending satellite observations with numerical models and in situ measurements. The Double U-Net model excels in capturing SST dynamics and detailed spatial patterns, offering sharper representations of ocean current-induced SST patterns than the interpolated outputs of Data Interpolating Empirical Orthogonal Functions (DINEOFs). Comparative analysis with buoy observations shows the Double U-Net model’s enhanced accuracy, with better correlation results and lower error values across most study areas. By analyzing SST at five key locations near Taiwan, the research highlights the Double U-Net’s potential for high-resolution SST reconstruction, thus enhancing our understanding of ocean temperature dynamics. Based on this method, we can combine more high-resolution satellite data in the future to improve the data-filling model and apply it to marine geographic information science.
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Differential Scanning Calorimetry (DSC) is a regular and powerful tool to measure the specific heat profile of various materials. In order to connect the measured profile to the properties of a particular protein, a model is required to fit. We discuss here the
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Differential Scanning Calorimetry (DSC) is a regular and powerful tool to measure the specific heat profile of various materials. In order to connect the measured profile to the properties of a particular protein, a model is required to fit. We discuss here the application of an exact two-state formula with its approximation and process the DSC experimental data on protein folding in water. The approximate formula relies on the smallness of the transition interval, which is different for each protein. With an example of the set of 33 different proteins, we show the practical validity of the approximation and the equivalence of exact and approximate two-state formulas for processing DSC data.
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High-strength steel (HSS) members with welded sections exhibit a notably lower residual compressive stress ratio compared with common mild steel (CMS) members. Despite this difference, current codes often generalize the findings from CMS members to HSS members, and the previous unified residual stress
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High-strength steel (HSS) members with welded sections exhibit a notably lower residual compressive stress ratio compared with common mild steel (CMS) members. Despite this difference, current codes often generalize the findings from CMS members to HSS members, and the previous unified residual stress models are generally conservative. This study focuses on the membrane residual stress distribution in Q690 steel welded box sections. By leveraging experimental results, the influence of section sizes and welding parameters on membrane residual stress was delved into. A larger plate size correlates with a decrease in the residual compressive stress across the section, with a more pronounced reduction observed in adjacent plates. Additionally, augmenting the number of welding passes tends to diminish residual stresses across the section. Results showed that membrane residual stress adhered to the section’s self-equilibrium, while the self-equilibrium in the plates was not a uniform pattern. A reliable residual stress simulation method for Q690 steel welded box sections was established using a three-dimensional thermal–elastic–plastic finite element model (3DTEFEM) grounded in experimental data. This method served as the cornerstone for parameter analysis in this study and set the stage for subsequent research. As a result, an accurate unified residual stress model for Q690 steel welded box sections was derived.
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This study investigated the aerosol particle properties and light absorption properties of brown carbon (BrC) by utilizing a seven-wavelength aethalometer, and analyzed NH4+, NO3−, SO42−, K+, K, organic carbon, elemental carbon, levoglucosan,
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This study investigated the aerosol particle properties and light absorption properties of brown carbon (BrC) by utilizing a seven-wavelength aethalometer, and analyzed NH4+, NO3−, SO42−, K+, K, organic carbon, elemental carbon, levoglucosan, and mannosan in PM2.5. The research was conducted in a rural area of Jeonnam, South Korea, during the winter season. In addition, the dithiothreitol assay-oxidative potential normalized to 9,10-phenanthrenequinone (QDTT-OP) was investigated throughout the study period. The absorption coefficient was found to be 2.6 to 5.6 times higher at 370 nm compared to 880 nm, suggesting the presence of light-absorbing substances in addition to black carbon (BC) particles. The estimated absorption coefficient of BrC370 was 29.9% of the total light absorption coefficient at 370 nm. Furthermore, BrC370 exhibited a strong affinity with levoglucosan while showing a weak correlation with K+, confirming the suitability of levoglucosan as a tracer for biomass burning. The QDTT-OP was 5.3 nM m−3, and highly correlated with the carbonaceous components levoglucosan and mannosan, suggesting a relatively high contribution of biomass combustion emissions to oxidative potential. Further research should be conducted to assess the health risks associated with future PM2.5 exposure related to biomass burning in the atmosphere.
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The interactions of metal ions with fulvic acids were investigated from the point of view of the thermodynamic aspects of complexation as well as the size and charge of the formed complexes. Thermodynamic aspects were studied by means of isothermal titration calorimetry. Particle
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The interactions of metal ions with fulvic acids were investigated from the point of view of the thermodynamic aspects of complexation as well as the size and charge of the formed complexes. Thermodynamic aspects were studied by means of isothermal titration calorimetry. Particle size distribution was determined by the method of dynamic light scattering and charge by the measurement of zeta potential. Complexation resulted in changes in particle size and charge. The particle size distribution was trimodal for fulvic acids and bimodal for fulvic complexes with calcium and magnesium, while copper–fulvic complexes had only one size fraction. The compensation of the negative charge of carboxylic and phenolic functional groups by positively charged metal ions resulted in an increase in zeta potential which became closer to zero in the case of copper–fulvic complexes. However, all metal–humic complexes behaved as colloidally unstable, which resulted in visually observable sedimentation. Calorimetric measurements provided positive values for changes in enthalpy, which indicated endothermic processes. In contrast, quantum chemical calculations as well as experiments with model compounds provided negative values indicating exothermic processes. Changes in Gibbs energy were determined as negative and changes in entropy as positive.
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Based on the post-earthquake investigation of the Beiling and Hanshen earthquakes, many welded rigid beam–column joints were found to exhibit brittle failure. The failure modes of the joint region and the overall steel frame structure under the action of the earthquake need to
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Based on the post-earthquake investigation of the Beiling and Hanshen earthquakes, many welded rigid beam–column joints were found to exhibit brittle failure. The failure modes of the joint region and the overall steel frame structure under the action of the earthquake need to be studied. The seismic performance of different types of weakened beam-end interior joints was investigated. The finite element method was verified by high-strength steel beam–column joint tests conducted by our research team. Finite element modeling of weakened steel beam flanges and weakened steel beam web joints was carried out based on the validated finite element modeling method. The joints were studied and analyzed using seismic parameters such as joint stress clouds, equivalent story shear–inter-story displacement ratio curves, panel zone bending moment–shear ratio curves, ductility, stiffness, and energy dissipation. The results of this study showed that honeycomb open hole-type joints exhibit a better deformation and energy dissipation capacity compared to open circular web hole-type joints. However, their load carrying capacity is reduced, which is mainly due to the larger area of the web openings. Additionally, double reduced beam section (DRBS) joints exhibit superior seismic performance and plastic hinge outward movement characteristics compared to single reduced beam section (RBS) joints. It was also found that the deformation and energy dissipation of DRBS joints and steel beam honeycomb hole-type joints are mainly borne by the beams, with the panel zone’s participation in energy dissipation accounting for a smaller proportion of the energy.
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In the five-phase-inverter adjustable speed system, a five-phase two-level inverter usually adopts the nearest-two vector SVPWM (NTV-SVPWM) or the nearest-four vector SVPWM (NFV-SVPWM). The former one has a high-output-current harmonic, which increases the power losses, while the latter one has a low harmonic,
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In the five-phase-inverter adjustable speed system, a five-phase two-level inverter usually adopts the nearest-two vector SVPWM (NTV-SVPWM) or the nearest-four vector SVPWM (NFV-SVPWM). The former one has a high-output-current harmonic, which increases the power losses, while the latter one has a low harmonic, but its sinusoidal voltage transfer ratio (VTR) is 0.812, which decreases load capacity. To improve the loading capacity and decrease the power losses of the five-phase-inverter adjustable speed system, a new space vector over-modulation method based on multi-vector weighting is proposed in this paper, and harmonic characteristics of the proposed over-modulation method are analyzed. The simulation results indicate that the proposed over-modulation method has a lower output voltage error than that with the traditional NFV-SVPWM and has a lower output current THD than that with the traditional NTV-SVPWM. The experimental results verify that the proposed method is correct and feasible.
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In this paper, we investigate the impact of COVID-19 on different performance measures and the risk of US Real Estate Investment Trusts (REITs) with different styles. Our findings suggest a phenomenon with compelling evidence of reduced performance without any significant changes in risk
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In this paper, we investigate the impact of COVID-19 on different performance measures and the risk of US Real Estate Investment Trusts (REITs) with different styles. Our findings suggest a phenomenon with compelling evidence of reduced performance without any significant changes in risk profile amidst the COVID-19 pandemic. Particularly, mortgage REITs (MREITs) appear to be more adversely affected compared to equity REITs (EREITs). We further explore and analyze the performance of specialized REITs in contrast to diversified REITs in the distinctive conditions presented by COVID-19. We find that diversification creates value for the entire sample period, whereas, during the COVID-19 pandemic, property type specialization helps, although the results are weakly significant. The findings on risk suggest investors’ short-run outlook on market reaction. These results remain robust to additional tests. The implications provide insight for investors as a reference to reallocate assets in their portfolios during uncertain times.
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Acute mountain sickness (AMS) is a common ailment in high-altitude areas caused by the body’s inadequate adaptation to low-pressure, low-oxygen environments, leading to organ edema, oxidative stress, and impaired intestinal barrier function. The gastrointestinal tract, being the first to be affected by ischemia
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Acute mountain sickness (AMS) is a common ailment in high-altitude areas caused by the body’s inadequate adaptation to low-pressure, low-oxygen environments, leading to organ edema, oxidative stress, and impaired intestinal barrier function. The gastrointestinal tract, being the first to be affected by ischemia and hypoxia, is highly susceptible to injury. This study investigates the role of Lactobacillus delbrueckii subsp. bulgaricus in alleviating acute hypoxic-induced intestinal and tissue damage from the perspective of daily consumed lactic acid bacteria. An acute hypoxia mouse model was established to evaluate tissue injury, oxidative stress, inflammatory responses, and intestinal barrier function in various groups of mice. The results indicate that strain 4L3 significantly mitigated brain and lung edema caused by hypoxia, improved colonic tissue damage, and effectively increased the content of tight junction proteins in the ileum, reducing ileal permeability and alleviating mechanical barrier damage in the intestines due to acute hypoxia. Additionally, 4L3 helped to rebalance the intestinal microbiota. In summary, this study found that Lactobacillus delbrueckii subsp. bulgaricus strain 4L3 could alleviate acute intestinal damage caused by hypoxia, thereby reducing hypoxic stress. This suggests that probiotic lactic acid bacteria that exert beneficial effects in the intestines may alleviate acute injury under hypoxic conditions in mice, offering new insights for the prevention and treatment of AMS.
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Extensive use of cement in the construction industry increases CO2 emissions and has a negative impact on the environment. In this work, recycled coarse aggregate (RCA) from construction and demolition wastes (C&DW) was used to fabricate sustainable pervious concrete (PC). In order
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Extensive use of cement in the construction industry increases CO2 emissions and has a negative impact on the environment. In this work, recycled coarse aggregate (RCA) from construction and demolition wastes (C&DW) was used to fabricate sustainable pervious concrete (PC). In order to mitigate the environmental hazards of excess cement waste and to improve the engineering properties of PC, silica fume (SF) and ground granulated blast-furnace slag (GGBS) were added. The effects of SF and GGBS on the compressive strength, permeability coefficient, porosity, and abrasion resistance of recycled aggregate pervious concrete (RAPC) were investigated. The results show that the incorporation of GGBS and SF effectively improves the compressive strength of RAPC but reduces the permeability coefficient and porosity. Moreover, due to the filling effect and pozzolanic activity, the incorporation of GGBS and SF significantly enhances the abrasion resistance of RAPC. Furthermore, the relationships between the compressive strength, permeability coefficient, porosity, and abrasion resistance of RAPC are clarified. The optimum replacement is achieved when the SF content is 7%, and the GGBS content is 20%, respectively, which results in the highest compressive strength (28.9 MPa) and the lowest permeability coefficient (1.2 mm/s) at 28 days, and the lowest mass loss rate (12.1%) after the Cantabro abrasion test.
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Quasi-interpolation is a powerful tool for approximating functions using radial basis functions (RBFs) such as Gaussian kernels. This avoids solving large systems of equations as in RBF interpolation. However, quasi-interpolation with Gaussian kernels on compact intervals can have significant errors near the boundaries.
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Quasi-interpolation is a powerful tool for approximating functions using radial basis functions (RBFs) such as Gaussian kernels. This avoids solving large systems of equations as in RBF interpolation. However, quasi-interpolation with Gaussian kernels on compact intervals can have significant errors near the boundaries. This paper proposes a quasi-interpolation method with Gaussian kernels using Chebyshev points and boundary corrections to improve the approximation near the boundaries. The boundary corrections use a linear approximation of the function beyond the interval to estimate the truncation error and add correction terms. Numerical studies on test functions show that the proposed method reduces errors significantly near boundaries compared to quasi-interpolation without corrections, for both equally spaced and Chebyshev points. The convergence and accuracy with the boundary corrections are generally better with Chebyshev points compared to equally spaced points. The proposed method provides an efficient way to perform quasi-interpolation on compact intervals while controlling the boundary errors. This study introduces a novel approach to quasi-interpolation modification, which significantly enhances convergence rates and minimizes errors at boundary points, thereby advancing the methods for boundary approximation.
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Male-perpetrated intimate partner violence (IPV) is a severe human rights violation that negatively affects women’s well-being worldwide. Although many studies have examined the factors influencing IPV, few have investigated the changes in attitudes toward IPV during rapid economic growth. Therefore, this study aimed
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Male-perpetrated intimate partner violence (IPV) is a severe human rights violation that negatively affects women’s well-being worldwide. Although many studies have examined the factors influencing IPV, few have investigated the changes in attitudes toward IPV during rapid economic growth. Therefore, this study aimed to clarify changes in attitudes toward husband-on-wife violence by gender, from 2007 to 2017, using individual data from the Indonesia Demographic and Health Surveys. The estimation results revealed that, despite being more accepting of IPV, young women, women living in rural areas other than Java and Bali, and women belonging to lower social classes have significantly increased their negative attitudes toward IPV over the past decade. Although negative attitudes toward IPV have increased significantly among men living in eastern Indonesia, men in their teens, 20s, and 30s and those living in Sumatra have become more accepting of IPV. This suggests that the overall awareness of IPV resistance among men has not increased. The acceptance of IPV is more prevalent among employed women in the middle and lower socioeconomic strata than among their unemployed counterparts. However, the reverse trend has become clearer among women in the upper strata over the past decade.
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Anomaly detection is the process of detecting unusual or unforeseen patterns or events in data. Many factors, such as malfunctioning hardware, malevolent activities, or modifications to the data’s underlying distribution, might cause anomalies. One of the key factors in anomaly detection is balancing
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Anomaly detection is the process of detecting unusual or unforeseen patterns or events in data. Many factors, such as malfunctioning hardware, malevolent activities, or modifications to the data’s underlying distribution, might cause anomalies. One of the key factors in anomaly detection is balancing the trade-off between sensitivity and specificity. Balancing these trade-offs requires careful tuning of the anomaly detection algorithm and consideration of the specific domain and application. Deep learning techniques’ applications, such as LSTMs (long short-term memory algorithms), which are autoencoders for detecting an anomaly, have garnered increasing attention in recent years. The main goal of this work was to develop an anomaly detection solution for an electrical machine using an LSTM-autoencoder deep learning model. The work focused on detecting anomalies in an electrical motor’s variation vibrations in three axes: axial (X), radial (Y), and tangential (Z), which are indicative of potential faults or failures. The presented model is a combination of the two architectures; LSTM layers were added to the autoencoder in order to leverage the LSTM capacity for handling large amounts of temporal data. To prove the LSTM efficiency, we will create a regular autoencoder model using the Python programming language and the TensorFlow machine learning framework, and compare its performance with our main LSTM-based autoencoder model. The two models will be trained on the same database, and evaluated on three primary points: training time, loss function, and MSE anomalies. Based on the obtained results, it is clear that the LSTM-autoencoder shows significantly smaller loss values and MSE anomalies compared to the regular autoencoder. On the other hand, the regular autoencoder performs better than the LSTM, comparing the training time. It appears then, that the LSTM-autoencoder presents a superior performance although it was slower than the standard autoencoder due to the complexity of the added LSTM layers.
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This study delves into an in-depth examination of the biomechanical characteristics of various materials commonly utilized in the fabrication of artificial ankle joints. Specifically, this research focuses on the design of an ankle joint resembling the salto-talaris type, aiming to comprehensively understand its
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This study delves into an in-depth examination of the biomechanical characteristics of various materials commonly utilized in the fabrication of artificial ankle joints. Specifically, this research focuses on the design of an ankle joint resembling the salto-talaris type, aiming to comprehensively understand its performance under different loading conditions. Employing advanced finite element analysis techniques, this investigation rigorously evaluates the stresses and displacements experienced by the designed ankle joint when subjected to varying loads. Furthermore, this study endeavors to identify the vibrating frequencies associated with these displacements, offering valuable insights into the dynamic behavior of the ankle joint. Notably, the analysis extends to studying random frequencies across three axes of motion, enabling a comprehensive assessment of directional deformities that may arise during joint function. To validate the effectiveness of the proposed design, a comparative analysis is conducted against the star ankle design, a widely recognized benchmark in ankle joint prosthetics. This comparative approach serves dual purposes: confirming the accuracy of the findings derived from the salto-talaris design and elucidating the relative efficacy of the proposed design in practical application scenarios.
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Insulin secretion from pancreatic β cells is a key pillar of glucose homeostasis, which is impaired under obesity and aging. Growth hormone secretagogue receptor (GHSR) is the receptor of nutrient-sensing hormone ghrelin. Previously, we showed that β-cell GHSR regulated glucose-stimulated insulin secretion (GSIS)
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Insulin secretion from pancreatic β cells is a key pillar of glucose homeostasis, which is impaired under obesity and aging. Growth hormone secretagogue receptor (GHSR) is the receptor of nutrient-sensing hormone ghrelin. Previously, we showed that β-cell GHSR regulated glucose-stimulated insulin secretion (GSIS) in young mice. In the current study, we further investigated the effects of GHSR on insulin secretion in male mice under diet-induced obesity (DIO) and streptozotocin (STZ)-induced β-cell injury in aging. β-cell-specific-Ghsr-deficient (Ghsr-βKO) mice exhibited no glycemic phenotype under DIO but showed significantly improved ex vivo GSIS in aging. We also detected reduced insulin sensitivity and impaired insulin secretion during aging both in vivo and ex vivo. Accordingly, there were age-related alterations in expression of glucose transporter, insulin signaling pathway, and inflammatory genes. To further determine whether GHSR deficiency affected β-cell susceptibility to acute injury, young, middle-aged, and old Ghsr-βKO mice were subjected to STZ. We found that middle-aged and old Ghsr-βKO mice were protected from STZ-induced hyperglycemia and impaired insulin secretion, correlated with increased expression of insulin signaling regulators but decreased pro-inflammatory cytokines in pancreatic islets. Collectively, our findings indicate that β-cell GHSR has a major impact on insulin secretion in aging but not obesity, and GHSR deficiency protects against STZ-induced β-cell injury in aging.
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Thermo-vortices (bright spots, blobs, swirls) in cosmic fluids (planetary atmospheres, or even black hole accretion disks) are sometimes observed as clustered into quasi-symmetrical quasi-stationary groups but conceptualized in models as autonomous items. We demonstrate—using the (analytical) Sharp Boundaries Evolution Method and a generic
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Thermo-vortices (bright spots, blobs, swirls) in cosmic fluids (planetary atmospheres, or even black hole accretion disks) are sometimes observed as clustered into quasi-symmetrical quasi-stationary groups but conceptualized in models as autonomous items. We demonstrate—using the (analytical) Sharp Boundaries Evolution Method and a generic model of a thermo-vorticial field in a rotating “thin” fluid layer in a spacetime that may be curved or flat—that these thermo-vortices may be not independent but represent interlinked parts of a single, coherent, multi-petal macro-structure. This alternative conceptualization may influence the designs of numerical models and image-reconstruction methods.
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Loop closure detection is an important component of the Simultaneous Localization and Mapping (SLAM) algorithm, which is utilized in environmental sensing. It helps to reduce drift errors during long-term operation, improving the accuracy and robustness of localization. Such improvements are sorely needed, as
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Loop closure detection is an important component of the Simultaneous Localization and Mapping (SLAM) algorithm, which is utilized in environmental sensing. It helps to reduce drift errors during long-term operation, improving the accuracy and robustness of localization. Such improvements are sorely needed, as conventional visual-based loop detection algorithms are greatly affected by significant changes in viewpoint and lighting conditions. In this paper, we present a semantic spatial structure-based loop detection algorithm. In place of feature points, robust semantic features are used to cope with the variation in the viewpoint. In consideration of the semantic features, which are region-based, we provide a corresponding matching algorithm. Constraints on semantic information and spatial structure are used to determine the existence of loop-back. A multi-stage pipeline framework is proposed to systematically leverage semantic information at different levels, enabling efficient filtering of potential loop closure candidates. To validate the effectiveness of our algorithm, we conducted experiments using the uHumans2 dataset. Our results demonstrate that, even when there are significant changes in viewpoint, the algorithm exhibits superior robustness compared to that of traditional loop detection methods.
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This paper investigates a novel nonconforming virtual element method (VEM) for solving the Kirchhoff plate obstacle problem, which is described by a fourth-order variational inequality (VI) of the first kind. In our study, we distinguish our approach by introducing new internal
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This paper investigates a novel nonconforming virtual element method (VEM) for solving the Kirchhoff plate obstacle problem, which is described by a fourth-order variational inequality (VI) of the first kind. In our study, we distinguish our approach by introducing new internal degrees of freedom to the traditional lowest-order nonconforming VEM, which originally lacked such degrees. This addition not only facilitates error estimation but also enhances its intuitiveness. Importantly, our novel nonconforming VEM naturally satisfies the constraints of the obstacle problem. We then establish an a priori error estimate for our novel nonconforming VEM, with the result indicating that the lowest order of our method achieves optimal convergence. Finally, we present a numerical example to validate the theoretical result.
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Very little identifiable research explores the factors impacting autistic students’ school motivation and how these factors may or may not affect their academic and well-being outcomes in secondary school and beyond, including post-secondary enrollment, employment, and their quality of life. Instead, research on
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Very little identifiable research explores the factors impacting autistic students’ school motivation and how these factors may or may not affect their academic and well-being outcomes in secondary school and beyond, including post-secondary enrollment, employment, and their quality of life. Instead, research on autism and inclusive education mainly focuses on the efficacy of interventions aimed at teaching skills related to sensory, communication, social, and behavior. Methods: A secondary analysis of survey data from an original mixed-method study was conducted to investigate how environmental, teacher, and peer factors are associated with autistic students’ school motivation. Eligible participants were between the ages of 15 and 21. In total, 72 participants (n = 72) completed an online survey to share their perspectives on their school experiences. Subsequently, linear regression analysis was conducted to answer the research question. Results: Participants who rated their schools as having pleasant physical spaces and felt that their peers understood them as a person had higher levels of school motivation. Teachers were not found to be significantly related to students’ school motivation. Participants who shared that typing was their preferred mode of communication were less motivated to attend school than students who preferred speaking communication. Conclusions: Environmental and peer factors are related to more than the day-to-day school experiences of autistic students; they are also related to their school motivation. These findings add to the existing literature on inclusive education and positive school outcomes for autistic students and offer additional explanations of the barriers that affect autistic students’ graduation from secondary school and interest in attending post-secondary education.
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The aim of this study was to collect data and analyze mortality among patients hospitalized with community-acquired infections in the Faroe Islands. A prospective observational study was conducted in the Medical Department of the National Hospital of the Faroe Islands from October 2013
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The aim of this study was to collect data and analyze mortality among patients hospitalized with community-acquired infections in the Faroe Islands. A prospective observational study was conducted in the Medical Department of the National Hospital of the Faroe Islands from October 2013 to April 2015. Cumulative all-cause, in-hospital, short-term, intermediate-term and long-term mortality rates were calculated. Kaplan–Meier survival curves comparing infection-free patients with infected patients of all severities and different age groups are presented. A log-rank test was used to compare groups. Mortality hazard ratios were calculated for subgroups using Cox regression multivariable models. There were 1309 patients without infection and 755 patients with infection. There were 51% female and 49% male patients. Mean age was 62.73 ± 19.71. Cumulative all-cause mortality and in-hospital mortality were highest in more severe forms of infection. This pattern remained the same for short-term mortality in the model adjusted for sex and age, while there were no significant differences among the various infection groups in regard to intermediate- or long-term survival after adjustment. Overall and short-term mortality rates were highest among those with severe manifestations of infection and those with infection compared to infection-free patients.
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Soccer athletic performance varies across a soccer season due to training and fatigue. In addition, it is known that core stability is linked with anterior cruciate ligament (ACL) injury risk but their variations over a season are unknown. The aim of the study
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Soccer athletic performance varies across a soccer season due to training and fatigue. In addition, it is known that core stability is linked with anterior cruciate ligament (ACL) injury risk but their variations over a season are unknown. The aim of the study was to determine the evolution of core stability, athletic performance, and ACL injury risk among young high-level soccer players at four key moments of a season: pre-season (PRE), start of season (START), mid-season (MID), and the end of the season (END). Core stability scores increased until mid-season, while ACL injury risk scores (measured during sidestep cuttings and single-leg landing) decreased thanks to an injury prevention program between START and MID. These results are in line with the literature, which demonstrates that a high level of core stability is linked to a low injury risk. Evolution of athletic performance was not consistent throughout the season, being dependent on the specific phases of training performed by the athletes. Therefore, assessing core stability, athletic performance, and ACL injury risk multiple times across a soccer season could help coaches to adapt their training programs properly.
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The aim of this study was to evaluate the effects of mechanical (pigeage, délestage and remontage) and oxygenation treatments on the phenolic and aromatic compounds and sensory characteristics of Teran wines. The experiment included a 20-day maceration period, during which the above-mentioned treatments
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The aim of this study was to evaluate the effects of mechanical (pigeage, délestage and remontage) and oxygenation treatments on the phenolic and aromatic compounds and sensory characteristics of Teran wines. The experiment included a 20-day maceration period, during which the above-mentioned treatments were applied, as well as the post-fermentation processes of pressing and first rack. The analysis of phenolic, chromatic and aroma compounds and the sensory characterization of the wines were used to describe the effects of the treatments investigated. After the observed maceration period, remontage resulted in wines with the highest total phenols (2682.0 ± 14.8 mg GAE/L). In contrast, délestage resulted in the lowest total phenols (2499.1 ± 17.6 mg GAE/L) and total anthocyanins (530.1 ± 2.8 mg/L) and had the strongest effects on chromatic characteristics. The post-fermentation processes (pressing, racking) showed similar trends and resulted in higher phenolic concentrations in the remontage wine, while the délestage was again characterized by lower total phenol and anthocyanin concentrations. In addition, the délestage wine contained a higher concentration of almost all analyzed esters and two higher alcohols (2-methylpropan-1-ol and 1-hexanol), while the remontage wine had the highest concentration of 2-phenylethanol and 3-methylbutyl acetate. Finally, maceration proved to be a key factor in defining the wines’ sensory characteristics, with the remontage-treated wine showing the best overall quality.
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Systemic sclerosis (SSc) is a chronic autoimmune connective tissue disease that affects more than 2 million people worldwide. It manifests through vasculopathy, an abnormal immunological response, and fibrosis leading to dysfunction of the multiple organs. The disease is categorized into two subtypes: limited
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Systemic sclerosis (SSc) is a chronic autoimmune connective tissue disease that affects more than 2 million people worldwide. It manifests through vasculopathy, an abnormal immunological response, and fibrosis leading to dysfunction of the multiple organs. The disease is categorized into two subtypes: limited cutaneous SSc and diffuse cutaneous SSc. Scleroderma can affect vital organs with respiratory, cardiac, renal, ocular, and dermatological complications. The ocular manifestations of the disease can occur in the anterior and posterior segments of the eye. Changes in the anterior segment related to the disease include eyelid skin remodeling, dry eye syndrome, and conjunctival abnormalities. The disease’s impact on the posterior segment of the eye mostly causes pathologies in the retinal microcirculatory system and abnormalities in the optic nerve. This review provides detailed insights into ocular complications associated with scleroderma.
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