Miracle-dz/UniFAR-FTUs huggingface dataset:
Influence of perceived organizational support on work engagement of university physical education teachers in Hubei Province, China

Physical education teachers in colleges and universities have the crucial responsibility of acting as mentors and guides for the healthy growth of students. The work engagement of these teachers affects the quality of higher education personnel training and health education. Based on the job demand-resource model, this study conducted a questionnaire survey on 500 physical education teachers in 20 colleges and universities in Hebei Province, China. The subjects were selected through convenience sampling. Out of the total, 456 valid questionnaires were recovered. The intermediary effect was tested through the AMOS model analysis and the Bootstrap method. The results revealed that the perceived organizational support of the participating physical education teachers in colleges and universities can positively affect their sense of teaching efficacy, which in turn positively affects work engagement and has a partial mediating effect on the relationship between perceived organizational support and work engagement.
Spectral clustering eigenvector selection of hyperspectral image based on the coincidence degree of data distribution

ABSTRACT Spectral clustering is a well-regarded subspace clustering algorithm that exhibits outstanding performance in hyperspectral image classification through eigenvalue decomposition of the Laplacian matrix. However, its classification accuracy is severely limited by the selected eigenvectors, and the commonly used eigenvectors not only fail to guarantee the inclusion of detailed discriminative information, but also have high computational complexity. To address these challenges, we proposed an intuitive eigenvector selection method based on the coincidence degree of data distribution (CDES). First, the clustering result of improved k-means, which can well reflect the spatial distribution of various types was used as the reference map. Then, the adjusted Rand index and adjusted mutual information were calculated to assess the data distribution consistency between each eigenvector and the reference map. Finally, the eigenvectors with high coincidence degrees were selected for clustering. A case study on hyperspectral mineral mapping demonstrated that the mapping accuracies of CDES are approximately 56.3%, 15.5%, and 10.5% higher than those of the commonly used top, high entropy, and high relevance eigenvectors, and CDES can save more than 99% of the eigenvector selection time. Especially, due to the unsupervised nature of k-means, CDES provides a novel solution for autonomous feature selection of hyperspectral images.
The nuclear option: Voting for the pan-European party Volt

Volt is a pan-European, Eurofederalist party that seeks to deepen and democratize European Union integration. It participated in elections in nine European countries and won representation in the Dutch Parliament and German constituency for the European Parliament. We examine Volt Netherlands, which studies the possibilities of a pan-European party. We look at the importance of its pro-European positions for voting for this party; this is an issue that all national branches of Volt share. We also examine the specific political opportunity structure of the Netherlands, where pro-nuclear environmentalism was an open niche. In this way, we weigh the importance of the party's pan-European appeal and the country-specific political opportunity structure. We show the importance of the country-specific factors for new party support and thus cast doubt on the ability of pan-European parties to mobilize voters all over Europe with the same message.
A visually meaningful image encryption algorithm based on P-tensor product compressive sensing and newly-designed 2D memristive chaotic map

The noise-like visual feature of cipher images produced by using the traditional image encryption technology explicitly reflects the presence of secret information. To overcome this issue, a visually meaningful image encryption algorithm is proposed based on a newly designed 2D memristive chaotic map, P-tensor product compressive sensing (PTP-CS) and discrete Hartley transform (DHT). For concreteness, a new two-dimensional discrete memristive chaotic map is first designed to provide highly unpredictable secret code streams while maintaining low time consumption. Second, the threshold processing and zigzag confusion operations are performed on the discrete wavelet coefficients of the plain image to meet the prerequisites for effective compression. Third, the intermediate secret information is obtained by utilizing PTP-CS in the compression layer. Information entropy and edge entropy are employed to adaptively identify the complex regions that are suitable for embedding due to inconspicuous visual degradation in the carrier image. Finally, the embedding of the secret information in the DHT domain of these regions is accomplished. Security test and performance analysis confirm that our algorithm has the advantage of a high balance between the encryption security and the decryption recovery, and exhibits excellent performance in important indicators such as visual quality, robustness and timeliness.
Fast Neighbor Discovery for Wireless Ad Hoc Network With Successive Interference Cancellation

Neighbor discovery (ND) is a key step in wireless ad hoc network, which directly affects the efficiency of wireless networking. Improving the speed of ND has always been the goal of ND algorithms. The classical ND algorithms lose packets due to the collision of multiple packets, which greatly affects the speed of the ND algorithms. Traditional methods detect packet collision and implement retransmission when encountering packet loss. However, they does not solve the packet collision problem and the performance improvement of ND algorithms is limited. In this paper, the successive interference cancellation (SIC) technology is introduced into the ND algorithms to unpack multiple collision packets by distinguishing multiple packets in the power domain. Besides, the multi-packet reception (MPR) is further applied to reduce the probability of packet collision by distinguishing multiple received packets, thus further improving the speed of ND algorithms. Six ND algorithms, namely completely random algorithm (CRA), CRA based on SIC (CRA-SIC), CRA based on SIC and MPR (CRA-SIC-MPR), scan-based algorithm (SBA), SBA based on SIC (SBA-SIC), and SBA based on SIC and MPR (SBA-SIC-MPR), are theoretically analyzed and verified by simulation. The simulation results show that SIC and MPR reduce the ND time of SBA by 69.02% and CRA by 66.03% averagely.
An Exposure Meter of Lijiang Fiber-fed High-Resolution Spectrograph

In 2016, an exposure meter was installed on the Lijiang Fiber-fed High-Resolution Spectrograph to monitor the coupling of starlight to the science fiber during observations. Based on it, we investigated a method to estimate the exposure flux of the CCD in real time by using the counts of the photomultiplier tubes (PMT) of the exposure meter, and developed a piece of software to optimize the control of the exposure time. First, by using flat-field lamp observations, we determined that there is a linear and proportional relationship between the total counts of the PMT and the exposure flux of the CCD. Second, using historical observations of different spectral types, the corresponding relational conversion factors were determined and obtained separately. Third, the method was validated using actual observation data, which showed that all values of the coefficient of determination were greater than 0.92. Finally, software was developed to display the counts of the PMT and the estimated exposure flux of the CCD in real-time during the observation, providing a visual reference for optimizing the exposure time control.
Pharmaceutical efficacy of novel human-origin Faecalibacterium prausnitzii strains on high-fat-diet-induced obesity and associated metabolic disorders in mice

Introduction Obesity and related metabolic issues are a growing global health concern. Recently, the discovery of new probiotics with anti-obesity properties has gained interest. Methods In this study, four Faecalibacte-rium prausnitzii strains were isolated from healthy human feces and evaluated on a high-fat diet-induced mouse model for 12 weeks. Results The F. prausnitzii strains reduced body weight gain, liver and fat weights, and calorie intake while improving lipid and glucose metabolism in the liver and adipose tissue, as evidenced by regulating lipid metabolism-associated gene expression, including ACC1, FAS, SREBP1c, leptin, and adiponectin. Moreover, the F. prausnitzii strains inhibited low-grade inflammation, restored gut integrity, and ameliorated hepatic function and insulin resistance. Interestingly, the F. prausnitzii strains modulated gut and neural hormone secretion and reduced appetite by affecting the gut-brain axis. Supplementation with F. prausnitzii strains noticeably changed the gut microbiota composition. Discussion In summary, the novel isolated F. prausnitzii strains have therapeutic effects on obesity and associated metabolic disorders through modulation of the gut-brain axis. Additionally, the effectiveness of different strains might not be achieved through identical mechanisms. Therefore, the present findings provide a reliable clue for developing novel therapeutic probiotics against obesity and associated metabolic disorders.
Research on an Adaptive Method for the Angle Calibration of Roadside LiDAR Point Clouds

Light Detection and Ranging (LiDAR), a laser-based technology for environmental perception, finds extensive applications in intelligent transportation. Deployed on roadsides, it provides real-time global traffic data, supporting road safety and research. To overcome accuracy issues arising from sensor misalignment and to facilitate multi-sensor fusion, this paper proposes an adaptive calibration method. The method defines an ideal coordinate system with the road’s forward direction as the X-axis and the intersection line between the vertical plane of the X-axis and the road surface plane as the Y-axis. This method utilizes the Kalman filter (KF) for trajectory smoothing and employs the random sample consensus (RANSAC) algorithm for ground fitting, obtaining the projection of the ideal coordinate system within the LiDAR system coordinate system. By comparing the two coordinate systems and calculating Euler angles, the point cloud is angle-calibrated using rotation matrices. Based on measured data from roadside LiDAR, this paper validates the calibration method. The experimental results demonstrate that the proposed method achieves high precision, with calculated Euler angle errors consistently below 1.7%.
Oxidative and Endoplasmic Reticulum Stress Represent Novel Therapeutic Targets for Choroideremia

Choroideremia (CHM) is a rare X-linked chorioretinal dystrophy, affecting the photoreceptors, retinal pigment epithelium (RPE) and choroid, with no approved therapy. CHM is caused by mutations in the CHM gene, which encodes the ubiquitously expressed Rab escort protein 1 (REP1). REP1 is involved in prenylation, a post-translational modification of Rab proteins, and plays an essential role in intracellular trafficking. In this study, we examined oxidative and endoplasmic reticulum (ER) stress pathways in chmru848 zebrafish and CHMY42X patient fibroblasts, and screened a number of neuroprotectants for their ability to reduce stress. The expression of the oxidative stress markers txn, cat and sod3a, and the ER stress markers bip, atf4 and atf6, were dysregulated in chmru848 fish. The expression of SOD2 was also reduced in CHMY42X fibroblasts, along with reduced BIP and increased CHOP expression. The lack of REP1 is associated with defects in vesicular trafficking, photoreceptor outer segment phagocytosis and melanosome transport, leading to increased levels of stress within the retina and RPE. Drugs targeting oxidative and ER stress pathways represent novel therapeutic avenues.
Stress and Sleep Quality among Engineering Students

Stress is a normal occurrence in human lives, and university students can never escape from experiencing stress at least once during their university years, during which they have to face a variety of stressors. Poor sleep quality happens to people of all ages worldwide, particularly university students. Numerous studies have reported that stress significantly correlates with sleep quality among university students from various courses. However, these variables were less explored by past researchers, specifically on engineering students. In order to explore more information on these variables among engineering university students, a cross-sectional, quantitative, correlational study is conducted to identify the relationship between stress and sleep quality among engineering students in Malaysia. A total of 272 undergraduate engineering students from three public universities in Malaysia were involved in the study. The Perceived Stress Scale (PSS-10) and Pittsburgh Sleep Quality Index (PSQI) were used. The result from the correlational analysis shows that there is a significant negative relationship between stress and sleep quality among engineering students. The study’s findings could be used as a reference for future studies and recommend interventions to improve students’ stress and sleep quality levels.
The relationship of player load and anaerobic performance in different football playing strategies

Background and Study Aim. The purpose of the present study is to determine the effect of player load on the anaerobic performance of soccer players. Material and Method. Eighty Turkish Super League U21 players (age:19.56±1.3 years, height: 180.3±2.1cm, weight: 75.9±3.7kg) were involved in this study. The players completed eight different 11v11 training games. While one team practiced the ball possession and “defense as a team” strategy, the other team implemented the counterattacking strategy. The formation was kept as “4-4-2”. The games were played as 2x20-min training matches. Maximum heart rate, player load, ratings of perceived exertion, high running speed, and sprint performances were analyzed. Pearson’s correlation analysis was used in determining the level of correlation between quantitative variables. Linear regression analyses were carried out to examine the effect of player load on anaerobic performance components in different strategies and positions. Results. Compared to tactical strategy, player load values were found to be different from all positions (P<0.05). It was observed that maximum hearth rate, ratings of perceived exertion, high running speed, and sprint data were correlated with player load data (p<0.05). Given the results achieved from the regression analysis, it was determined that an increase in player load data caused an increment in these data. Conclusions. In conclusion, it was observed that player load data affect position-specific anaerobic performance in football. It is thought that the use of the data related to player load, acceleration, and deceleration in the training planning in accordance with the positions of players and the team strategies will increase the performance of the athlete.
La circulation thermohaline de la Mer Méditerranée sous les climats présents et futurs

The thermohaline circulation (THC) of the Mediterranean Sea is controlled by two main atmospheric variabilities. The first one results from strong atmospheric events localized in space and time as the Eastern Mediterranean Transient (EMT). This variability is defined as “decadal”. The second one depends on the global climate of the Earth and involves longer space and time scales. This variability is referred to as “climatic”. In this thesis, we study the THC of the Mediterranean Sea under both variabilities using a numerical oceanic model of the Mediterranean Sea of resolution 1/8 (MED8). First, a diagnosis for water mass formation is set up in order to quantify changes. The impact of the penetration of the solar flux on water mass formation is then analyzed. This impact is of importance during spring and summer leading to a significant destruction of the waters formed in winter. The study of the “decadal” variability is then conducted by forcing MED8 with a random distribution of the high-resolution ECMWF analysis. During the last ten years of the simulation, a succession of cold winters over the Aegean Sea leads to anomalous convection. The detailed analysis of this event reveals the formation of very dense waters (> 29.3 σθ) and a reversal of the THC in the Aegean Sea. This simulation under “present” climate conditions is then used as a control simulation for the study of the “climatic” variability. The aim of this study is to characterize the THC changes in the context of climate change (A2 scenario of the IPCC). Three sensitivity experiments are thus realized using the atmospheric anomalies of global coupled models (IPSL, CNRM et GFDL) realizing scenario experiments. The results show an increase in the basin temperature ranging between 0.3 C (IPSL) and 0.5 C (GFDL) and an increase of the salinity between 300 and 800m. The intensity of the THC is also decreased by 10 to 20% and deep water mass formation is interrupted.
Virtual Reality Versus Flatscreen Pornography: Correlations and Effects on Relationship Satisfaction, Rape-Myth Acceptance, and Problematic Use

Abstract Traditional pornography use on a flatscreen (FS) is associated with lower relationship satisfaction, greater rape-myth acceptance (RMA), and problematic pornography use. Increasingly, immersive media technologies, such as virtual reality (VR), are transforming the way people consume and are potentially influenced by pornography. Spatial and social presence help explain differences between VR and FS in other media contexts and are therefore considered in the present study. This research examines effects and associations of VR pornography compared to FS pornography. A two-phase study was conducted to investigate how relationship satisfaction, RMA, and problematic pornography use vary between FS and VR formats. Study 1 used a survey to assess associations between use of VR pornography and relationship satisfaction, RMA, and problematic pornography use. Study 2 employed a 2 (modality: VR or FS) x 2 (masturbation: restricted or unrestricted) between-subjects online experiment. After the manipulation, participants completed a questionnaire. In both study phases, results suggest that consuming VR pornography is associated with less relationship satisfaction. Both RMA and problematic pornography use were associated with VR pornography use in Study 1, but there were no effects in Study 2. The findings presented here elucidate potential impacts of VR pornography use compared to FS consumption.
An integrative phenology and climatic suitability model for emerald ash borer

Introduction Decision support models that predict both when and where to expect emerald ash borer (EAB), Agrilus planipennis Fairmaire (Coleoptera: Buprestidae), are needed for the development and implementation of effective management strategies against this major invasive pest of ash (Fraxinus species) in North America and other regions such as Europe. We present a spatialized model of phenology and climatic suitability for EAB for use in the Degree-Days, Risk, and Phenological event mapping (DDRP) platform, which is an open-source decision support tool to help detect, monitor, and manage invasive threats. Methods We evaluated the model using presence records from three geographic regions (China, North America, and Europe) and a phenological dataset consisting primarily of observations from the northeastern and midwestern United States. To demonstrate the model, we produced phenological event maps for a recent year and tested for trends in EAB’s phenology and potential distribution over a recent 20-year period. Results Overall, the model exhibited strong performance. Presence was correctly estimated for over 99% of presence records and predicted dates of adult phenological events corresponded closely with observed dates, with a mean absolute error of ca. 7 days and low estimates of bias. Climate stresses were insufficient to exclude EAB from areas with native Fraxinus species in North America and Europe; however, extreme weather events, climate warming, and an inability for EAB to complete its life cycle may reduce suitability for some areas. Significant trends toward earlier adult emergence over 20 years occurred in only some areas. Discussion Near real-time model forecasts for the conterminous United States are available at two websites to provide end-users with decision-support for surveillance and management of this invasive pest. Forecasts of adult emergence and egg hatch are particularly relevant for surveillance and for managing existing populations with pesticide treatments and parasitoid introductions.
Weather variability, climatic change, and soybean production

A crop/weather model was used to determine the effect of changing climate and weather variability on soybean production in the Corn Belt. A cooling trend from the 1930s to the 1970s was accompanied by an upward trend in July plus August rainfall. There was decreased weather variability from the 1930s to 1973 and greatly increased weather variability after 1973. Improved weather from 1930 to 1972 increased soybean yields 3 bushels/acre. Higher intensity rainfalls increased in Illinois and Iowa after 1970.
A Novel Visual Scale Recovery for Resource-Limited Platform Using Single-Point Laser and Spatial Constraints

Motion estimation of vision-only has no absolute scale, which leads to unmeasurable scale and scale drift. Existing methods of visual scale recovery are either costly or complex, making it difficult to be widely used in resource-limited industries. A lightweight and low-cost method of scale recovery is urgently needed for low-configuration platforms. We innovatively use a camera and an invisible single-point laser transmitter to achieve six-degree-of-freedom (DOF) state estimation, which has minimal sensor requirements for visual scale recovery in terms of size, weight, power, and computational power consumption. It involves the incorporation of a laser into the camera’s field of view and uses a certain spatial relationship between the laser and the camera as a prior constraint for introducing an absolute scale. To address the problem that the laser spot is not visible and cannot be predicted, a background matching method was designed to achieve visual projection matching. To increase the robustness of the engineering, a dual-thread scale estimation method was developed to ensure the continuity and accuracy of scale recovery. The verification conducted with our hardware module and recorded datasets confirmed that the proposed method accurately recovers an absolute scale and controls scale drift. Compared with ORB-SLAM3 and VINS-Mono, which are currently the most concise schemes, the method put forward in this work reduces computational power consumption by more than 54%. Finally, the laser transmitter costs less than U.S. ${\$}$ 10. These features render the proposed method an efficient and affordable approach for visual scale recovery.