Miracle-dz/UniFAR-FTUs huggingface dataset:
A Finite Element/Lagrange Approach to Modeling Lightweight Flexible Manipulators

This paper presents a finite element/Lagrangian approach for the mathematical modeling of lightweight flexible manipulators. Each link of the manipulator is treated as an assemblage of a finite number of elements for each of which kinetic and potential energies are derived. These elemental kinetic and potential energies are then suitably combined to derive the dynamic model for the system. It is contended that satisfactory modeling and analysis of the manipulator dynamics can lead to the use of advanced control techniques to solve some of the problems associated with the flexure of otherwise attractive lightweight manipulator arms. Detailed model development and simulation results for the case of a two-link manipulator system are presented.
Statistical Analyses of the Non-Uniform Longitudinal Temperature Distribution in Steel Box Girder Bridge

The frequently conventional assumption that bridge temperature is uniformly distributed on long-span bridges could lead to uncertainty when analyzing temperature effects. This study investigated the surface temperature of steel box girders on a long-span suspension bridge, emphasizing the distribution characteristics in the longitudinal (spanwise) direction. The girder surface temperature distribution was monitored using the long-term structural health monitoring system (SHMS). First, the probability density functions (PDF) of the girder surface temperature were analyzed. The results showed that the PDFs had bimodal characteristics and could be well-fitted using the weighted superposition of two normal distributions. Meanwhile, there was an obvious difference between the PDFs of the measuring points at different longitudinal sections of the bridge, which is inconsistent with the assumption that the temperature was uniformly distributed in the longitudinal direction. Subsequently, the longitudinal distributions of the girder surface temperature were statistically analyzed, and polynomial functions were introduced to fit the distribution curves along the left and right sides of the mid-span. A correlation analysis was then performed, highlighting the variability in temperature in the longitudinal direction. Additionally, the longitudinal temperature distribution pattern could be summarized as (i) the highest in the mid-span, the lowest in the tower, and increasing along the side span; (ii) there were also significant differences between the left and right sides of the mid-span. Finally, the time- and space- distributions of the temperature were studied, and a contour map was displayed. The results showed that the girder surface temperature had significant three-dimensional spatial characteristics and was not only non-uniformly distributed in space but also in time. This work is useful for a more accurate analysis of temperature effects on long-span bridges.
THE BINARY NATURE OF CH-LIKE STARS

Yamashita has described a group of early carbon stars with enhanced lines of barium that resemble the CH stars but have low radial velocities. It is not clear whether they represent a class of stars separate from early R stars. Radial-velocity measurements and abundance analyses are applied in order to clarify the evolutionary status of CH-like stars. Radial-velocity monitoring was performed over a time interval of about 10 years. Abundance analysis was carried out using high-resolution spectra and the method of atmospheric models for three CH-like candidate stars. The radial-velocity monitoring confirmed regular variations for all of the classified CH-like stars, except for two, in support of their binary nature. The calculated orbital parameters are similar to those observed for barium stars in the disk of the Galaxy and their counterparts in the halo, that is, the CH stars. The relatively low luminosity of CH-like stars and the overabundance of s-process elements in the atmospheres are in agreement with a mass-transfer scenario from the secondary—an AGB star in the past. The kinematic data and metallicities support the idea that CH-like stars are thin/thick-disk population objects.
Preparation and Application Progress of Imprinted Polymers

Due to the specific recognition performance, imprinted polymers have been widely investigated and applied in the field of separation and detection. Based on the introduction of the imprinting principles, the classification of imprinted polymers (bulk imprinting, surface imprinting, and epitope imprinting) are summarized according to their structure first. Secondly, the preparation methods of imprinted polymers are summarized in detail, including traditional thermal polymerization, novel radiation polymerization, and green polymerization. Then, the practical applications of imprinted polymers for the selective recognition of different substrates, such as metal ions, organic molecules, and biological macromolecules, are systematically summarized. Finally, the existing problems in its preparation and application are summarized, and its prospects have been prospected.
Deep clustering for abdominal organ classification in ultrasound imaging

Abstract. Purpose The purpose of this study is to examine the utilization of unlabeled data for abdominal organ classification in multi-label (non-mutually exclusive classes) ultrasound images, as an alternative to the conventional transfer learning approach. Approach We present a new method for classifying abdominal organs in ultrasound images. Unlike previous approaches that only relied on labeled data, we consider the use of both labeled and unlabeled data. To explore this approach, we first examine the application of deep clustering for pretraining a classification model. We then compare two training methods, fine-tuning with labeled data through supervised learning and fine-tuning with both labeled and unlabeled data using semisupervised learning. All experiments were conducted on a large dataset of unlabeled images (nu = 84967) and a small set of labeled images (ns = 2742) comprising progressively 10%, 20%, 50%, and 100% of the images. Results We show that for supervised fine-tuning, deep clustering is an effective pre-training method, with performance matching that of ImageNet pre-training using five times less labeled data. For semi-supervised learning, deep clustering pre-training also yields higher performance when the amount of labeled data is limited. Best performance is obtained with deep clustering pre-training combined with semi-supervised learning and 2742 labeled example images with an F1-score weighted average of 84.1%. Conclusions This method can be used as a tool to preprocess large unprocessed databases, thus reducing the need for prior annotations of abdominal ultrasound studies for the training of image classification algorithms, which in turn could improve the clinical use of ultrasound images.
Numerical simulation of harmonic, and trapped, Rossby waves in a channel on the midlatitude β‐plane

The applicability of two competing wave theories of the rotating shallow‐water equations, the harmonic planetary waves and the trapped planetary waves, is examined by solving the equations numerically in a zonal channel on the midlatitude β‐plane. The examination is carried out by initializing the numerical shallow‐water solver by harmonic and trapped waves and comparing the temporal evolution to that expected from the corresponding wave theory. The simulations confirm that harmonic waves provide accurate approximations for the temporal evolution in narrow channels while trapped waves do so in wide channels. The transition from a narrow channel to a wide channel occurs when the non‐dimensional number L2cot⁡ϕ0aRd21/3 (where L is the channel width, Rd is the radius of deformation, a is Earth's radius and ϕ0 is the latitude of the centre of the channel) is increased above a threshold value that larger than 4 and that depends on the meridional mode number of the trapped wave. Numerical solutions of the nonlinear equations show that, for the same wave amplitude, trapped waves approximate the nonlinear solutions in a wide channel for much longer times than harmonic waves in a narrow channel.
A new global tree-cover percentage map using MODIS data

ABSTRACT Global tree-cover percentage is an important parameter used to understand the global environment. However, the available global percentage tree-cover products are few. Producing a new global-scale data set facilitates comparison analysis among maps. Our study was undertaken to map tree-cover percentage on a global scale with better accuracy than previous studies. In this study, we estimated the tree-cover percentage on a global scale at a pixel size of 500 m using a modified supervised regression tree algorithm from the Moderate Resolution Imaging Spectroradiometer (MODIS) data of 2008. Training data were derived from high-resolution images displayed in Google Earth and created by linear mixture simulation. The estimation model was modified to fit the reference data, which were randomly collected from the global area. The estimation result was validated at 1106 random sample points. The root mean square error (RMSE) between estimated and observed tree cover was 13.8%. The produced map was also compared with existing global data sets. The RMSE of our result was better than that of two existing global percentage tree-cover data sets (about 1.8% and 9.2% lower than Vegetation Continuous Fields MOD44B data set and Global Map – Percent Tree Cover data set, respectively). In our result and all other data sets, the accuracy was lower for forests than for other areas. When the produced map was compared with the Vegetation Continuous Fields MOD44B data set, the low agreement between them was concentrated in closed forests of Colombia, India, and Indonesia, and closed to open forests of Central Africa.
How does skin colour affect the therapeutic relationship in art psychotherapy?

ABSTRACT A recent seismic shift has brought issues of race and privilege into the collective consciousness, namely the global pandemic and the Black Lives Matter protests in 2020. This article looks at the consequences of not addressing power and White privilege in the art therapy room. Adopting an intersectional self-reflexive approach, this article presents my experience as a trainee art psychotherapist working in multicultural inner-city schools and argues for the prioritisation of addressing power and White privilege within art therapy practice. Using clinical vignettes I reflect on my own relationship with White privilege and consider how this might disrupt the formation of a therapeutic relationship. My experience aligned with much of the relevant literature, that to better understand and possibly dismantle damaging occurrences of power and White privilege in art therapy, more work and attention must be paid to this area. This includes current literature as well as developing our knowledge through future research that incorporates the voices of service users. Training in intersectionality and social justice are recommended to support the profession with facing up to the existence of White privilege. In addition, a compassionate space must be created to reflect on White privilege and fragility, so the work of countering the dominant narrative and educating the privileged does not fall only to those who have been marginalised and oppressed. Plain-language summary Issues of race and privilege have been brought into the collective consciousness through the global pandemic and the Black Lives Matter protests in 2020. This paper looks at the effect of not addressing power and White privilege in the therapy room and argues for the power and privilege that comes from being White to be reflected on as a priority in art therapy practice. To do this I have used my own experience to present my personal journey alongside relevant literature. Drawing on experience from my work in inner-city schools I examine my own relationship with being White and consider how this might disrupt the formation of a therapeutic relationship. I agree with much of the relevant literature, that to better understand and possibly dismantle damaging occurrences of power and White privilege in art therapy, more work and attention must be paid to this area. This includes current literature as well as developing our knowledge through future research that incorporates the voices of service users. To support the profession with facing up to the existence of White privilege I recommend training in how wider systems affect an individual’s varied and intersecting experiences of disadvantage and oppression, and the effect this has on that individual. In addition, a compassionate space must be created to reflect on White privilege and fragility, so the work of countering the dominant narrative and educating the privileged does not fall only to those who have been marginalised and oppressed.
Adaptive Fuzzy Descriptor Sliding Mode Observer‐based Sensor Fault Estimation for Uncertain Nonlinear Systems

A sensor fault estimation method is proposed for a general class of uncertain nonlinear systems. Taking the sensor faults as auxiliary states, an augmented descriptor system is constructed. For this augmented descriptor system, an adaptive fuzzy proportional‐derivative sliding mode observer is designed to estimate the sensor faults and states, simultaneously. Adaptive fuzzy systems based on the universal approximation theorem are used to approximate the nonlinearities. Thus, the nonlinearities can be unknown and the Lipschitz assumption can be utterly relieved. To relax the requirement of knowing the bound of uncertainties, an adaptive gain for the sliding mode term is used. The semi‐global asymptotic convergence of the proposed fault estimation observer is proved using the Lyapunov approach. The proposed method is applied to a highly nonlinear mathematical model with both bounded and unbounded sensor faults. Simulation results show the satisfactory performance of the proposed method.
A Simple Parameterization of Cloud Water Related Variables for Use in Boundary Layer Models

Abstract A simple parameterization of cloud water related variables has been developed which can be used in meteorological models that use a prognostic equation for the turbulent kinetic energy. Based on the results of large-eddy simulations (LES), expressions are derived for the liquid water flux, the partial cloudiness, and the cloud water content as a function of the normalized saturation deficit. With these relations, which are based on LESs ranging from situations with small to moderate amount of cumulus clouds to a stratocumulus case, no further knowledge about distribution functions or skewness is needed.
Face Recognition Model Optimization Research Based on Embedded Platform

The development of information technology has promoted the expansion of the application field of facial recognition technology. Its mainstream recognition methods rely on deep learning algorithms for calculation, but the problem of large data computation brought by its system makes it difficult to apply to embedded platform devices. As a result, this study focuses on improving recognition systems built on lightweight backend networks and builds an embedded platform system environment using multi-scale feature fusion, anchor box size optimization, the addition of channel attention mechanism weighted features, affine face alignment, and file compilation. The experimental results showed that when the number of iterations was 300, the loss value (0.46) of the improved embedded algorithm was much smaller than that of other comparison algorithms (1.42, 1.73, 2.01), and its ACC value (0.924) was significantly better than other comparison algorithms (0.915, 0.909, 0.894). The minimum system testing time consumedwas7 ms. This deep learning embedded facial recognition algorithm has high recognition accuracy, a fast running speed, and is less limited by environmental conditions and data types. It is ideally suited for use in embedded hardware devices, broadening the scope of equipment matching and facial recognition algorithms’ applications. As a result, it is better suited to satisfy the demands of embedded devices and massive data processing jobs.
Social Media Publishing Strategies of German Newspapers: Content Analysis of Sports Reporting on Social Networks by German Newspapers—Results of the 2021 Social Media International Sports Press Survey

Newspaper sports departments in Germany are reacting to changes in social media by expanding their offerings and employing a variety of publishing and engagement strategies. In this constantly evolving media environment, it is important to understand how newsrooms utilize social media to inform their audiences. This study examines the approaches German newspapers apply to publishing sports content on social media, and outlines how users interact with these posts. In analyzing these aspects, this paper applies theoretical elements of agenda setting and audience engagement, gender in media, and quality and diversity of published content. Social media posts were examined across eight German publications, totaling 3633 posts from Twitter and Facebook. Results in the study, which is part of the global 2021 Social Media International Sports Press Survey, highlighted how most of the content published by German newspapers on social media aimed to redirect users to the publications’ websites. The findings also reflect how social media is used less as an editorial space and more as part of a campaign to increase the audience. These results demonstrate challenges for the quality of sports coverage distributed via social networks in Germany.
Global Finite-time Stabilization of Nonlinear Integrator Systems Subject to Input Saturation

By utilizing finite-time control technique,a global finite-time control scheme is proposed for a class of nonlinear integrator systems subject to input saturation.First of all,based on finite-time Lyapunov stability theory,a global finitetime recursive stabilizing controller is presented.Then by combining the saturated function with the recursive controller,a saturated controller is developed.Rigorous mathematical proof shows that under the saturated controller,the closed loop system is globally finite-time stable.Simulation results verify the e? ectiveness of the proposed method.
Effects of drought stress on the oxidation of the reaction center chlorophyll of photosystem I and grain yield in paddy-field grown rice plants

ABSTRACT Drought is a serious abiotic stress that leads to decreased yield. In pot experiments, the reaction center chlorophyll of photosystem I (PSI) (P700) has been reported to be oxidized in response to drought stress. In the present study, we examined whether drought stress that decreases grain yield was detected by P700 oxidation in paddy-field-grown rice (Oryza sativa L.) plants. The P700 reduction and SPAD values were also evaluated. Drought stress was imposed by the prolonged mid-season drainage in 2019 and 2020. P700 oxidation was measured at saturated CO2 levels before heading. P700 oxidation was not stimulated in the 2019-drought plots. In contrast, P700 oxidation was stimulated in the 2020-drought plot. However, this phenomenon in 2020 was primarily accounted for by decreases in total leaf-N levels, as previously observed in the rice plants grown under low N availability. Rough rice yields and ratios of filled spikelets tended to decrease in the drought plots. Therefore, drought stress responsible for a decrease in grain yields could not be directly detected by P700 oxidation in paddy-field-grown rice plants, whereas the P700 oxidation responded to changes in total leaf-N levels due to the drought stress treatment. The same conclusion was drawn for the P700 reduction and SPAD value.
Breathlessness Predicts Mortality in Adults: A Systematic Review and Meta-Analysis

Breathlessness is a commonly encountered symptom, and although its relationship with mortality is well established for many conditions, less clear is this relationship in healthy adults. This systematic review and meta-analysis examines whether breathlessness is associated with mortality in a general population. This is important in understanding the impact of this common symptom on a patient's prognosis. This review was registered with PROSPERO (CRD42023394104). Medline, EMBASE, CINAHL and EMCARE were searched for the terms ‘breathlessness’ and ‘survival’ or ‘mortality’ on January 24, 2023. Longitudinal studies of >1,000 healthy adults comparing mortality between breathless and non-breathless controls were eligible for inclusion. If an estimate of effect size was provided, studies were included in the meta-analysis. Eligible studies underwent critical appraisal, data extraction and risk of bias assessment. A pooled effect size was estimated for the relationship between the presence of breathlessness and mortality and levels of severity of breathlessness and mortality. Of 1,993 studies identified, 21 were eligible for inclusion in the systematic review and 19 for the meta-analysis. Studies were of good quality with a low risk of bias, and the majority controlled for important confounders. Most studies identified a significant relationship between the presence of breathlessness and increased mortality. A pooled effect size was estimated, with the presence of breathlessness increasing the risk of mortality by 43% (risk ratio (RR): 1.43, 95% confidence interval (CI): 1.28-1.61). As breathlessness severity increased from mild to severe, mortality increased by 30% (RR: 1.30, 95% CI: 1.21-1.38) and 103%, respectively (RR: 2.03, 95% CI: 1.75-2.35). The same trend was seen when breathlessness was measured using the modified Medical Research Council (mMRC) Dyspnoea Scale: mMRC grade 1 conferred a 26% increased mortality risk (RR: 1.26, 95% CI: 1.16-1.37) compared with 155% for grade 4 (RR: 2.55, 95% CI: 1.86-3.50). We conclude that mortality is associated with the presence of breathlessness and its severity. The mechanism underlying this is unclear and may reflect the ubiquity of breathlessness as a symptom of many diseases.
Robust Scene Matching Method based on Binary Coding and Phase Correlation

By combining binary coding with phase correlation,a robust scene matching method is proposed.The sensed image and the reference sub-image are coded in binary numbers by the use of increment and decrement information of the pixels' values in the main diagonal of each 2×2 window.The binary-coded sensed image can be located in the reference image by computing the value of the phase correlation functions.Theoretical analysis and simulation experiments show the effectiveness of the algorithm in matching images with partial occlusion,intensity or contrast changes and complex noise corruptions,etc.
Exploring vocational students' satisfaction with online learning

This study aimed to explore the factors that influence vocational students' perceptions of their online learning experiences and assess the quality of online learning that has an impact on student satisfaction. This research used structural equation modeling and partial least square (PLS-SEM) analysis. The purposive sampling technique was chosen to determine the sample of respondents. A total of 3206 students who participated in online learning from various vocational schools in Indonesia filled out an online survey. The results indicate that communication, digital media, interaction, facilities and tutorials have a direct effect on the quality of online learning. Schools that offer online education must prioritize the essential factors required for successful implementation to ensure that students have an enjoyable online learning experience. Teachers should focus on improving the quality of online learning to increase student satisfaction with it. Furthermore, teachers should consider the findings of this research when developing strategies for vocational education in online settings.