Miracle-dz/UniFAR-FTUs huggingface dataset:
Video Global Motion Compensation Based on Affine Inverse Transform Model

Global motion greatly increases the number of false alarms for object detection in video sequences against dynamic backgrounds. Therefore, before detecting the target in the dynamic background, it is necessary to estimate and compensate the global motion to eliminate the influence of the global motion. In this paper, we use the SURF (speeded up robust features) algorithm combined with the MSAC (M-Estimate Sample Consensus) algorithm to process the video. The global motion of a video sequence is estimated according to the feature point matching pairs of adjacent frames of the video sequence and the global motion parameters of the video sequence under the dynamic background. On this basis, we propose an inverse transformation model of affine transformation, which acts on each adjacent frame of the video sequence in turn. The model compensates the global motion, and outputs a video sequence after global motion compensation from a specific view for object detection. Experimental results show that the algorithm proposed in this paper can accurately perform motion compensation on video sequences containing complex global motion, and the compensated video sequences achieve higher peak signal-to-noise ratio and better visual effects.
Combination of plyometric and ladder drill: Its impact on improving speed, agility, and leg muscle power in badminton

This research aims to determine the impact of a combination of plyometric and ladder drill training methods in increasing leg muscle speed, agility, and power. This research is a quantitative study with a quasi-experimental type and uses a nonequivalent control group design. Purposive sampling technique was used from 36 trained male students aged 12-16 years old from junior high school 1 to 36 years old badminton students. The research subjects were divided into three groups, namely TR (tuck jump-double leg run), SH (squat jump-double leg hop), and C (conventional exercise), which were divided using matched ordinal pairing. Each group consists of twelve students doing treatment with a frequency of three days a week for six weeks. The research instruments used were the 30-meter sprint, agility T-test, and Jump MD. Data collection was carried out twice during the pretest and posttest. Data analysis techniques using Manova and post hoc tests. The Manova test results showed significant differences in the three groups' increasing speed, agility, and leg muscle power simultaneously. The post hoc test showed that the TR and SH groups differed significantly from the C group (p<0.05).
Qam Receiver For Rayleigh Fading Channel

Rayleigh fading is a statistical model for the effect of a propagation environment on a radio signal, such as that used by wireless devices. The M state QAM contains M possible states for the signal. It can transmit k bits of information during each symbol period. The binary data stream is pre-processed before the modulation process. Then it performs a bit-to-symbol mapping. Binary data is then gray coded and then modulated by modulator. The modulated signal is up-sampled and filtered by square root raised cosine filter in the transmitter. Due to the channel the signal transmitted gets corrupted by the disturbances present in it. Further the received signal is filtered by the square root raised cosine filter to remove a portion of the signal in account for the filter delay in order to make a BER comparison. At receiver the signal received is down sampled and equalized by the RLS equalizer. The filtered signal is demodulated to obtain the transmitted signal.
Supraorbital artery: Anatomical variations and neurosurgical applications

Background: The supraorbital artery (SOA) originates from the ophthalmic artery in a superomedial aspect of the orbit, exiting through the supraorbital groove to emerge onto the forehead. The SOA has important neurosurgical considerations regarding different approaches and bypasses. The SOA is poorly described in the standard anatomical textbooks. Therefore, we present this article to describe the anatomical variations of the SOA and their implications on the neurosurgical field. Methods: We conducted a literature review in PubMed and Google Scholar databases to review the existing literature describing the SOA anatomy and its neurosurgical applications. Results: While reading the available articles and original works regarding SOA, we identified 22 studies that discuss the SOA. We noticed the anatomical variations of the SOA in terms of origin, course, diameter, branches, depth, and distance in relation to the midline and vertical glabellar line. We also discussed certain applications of SOA and its importance in neurosurgical approaches, bypass, photoplethysmography, aneurysms, and reconstruction of cranial fossa defects. Conclusion: The variable anatomy of the SOA has a paramount impact on performing different neurosurgical approaches. Therefore, cadaveric studies of the SOA are important to explore potential methods for the preservation of the artery in different neurosurgical applications.
Invasive alien plants are phylogenetically distinct from other alien species across spatial and taxonomic scales in China

Introduction Phylogenetic relatedness is one of the important factors in the community assembly process. Here, we aimed to understand the large-scale phylogenetic relationship between alien plant species at different stages of the invasion process and how these relationships change in response to the environmental filtering process at multiple spatial scales and different phylogenetic extents. Methods We identified the alien species in three invasion stages, namely invasive, naturalized, and introduced, in China. The occurrence records of the species were used to quantify two abundance-based phylogenetic metrics [the net relatedness index (NRI) and the nearest taxon index (NTI)] from a highly resolved phylogenetic tree. The metrics were compared between the three categories of alien species. Generalized linear models were used to test the effect of climate on the phylogenetic pattern. All analyses were conducted at four spatial scales and for three major angiosperm families. Results We observed significantly higher NRI and NTI values at finer spatial scales, indicating the formation of more clustered assemblages of phylogenetically closely related species in response to the environmental filtering process. Positive NTI values for the invasive and naturalized aliens suggested that the presence of a close relative in the community may help the successful naturalization and invasion of the introduced alien species. In the two-dimensional phylogenetic space, the invasive species communities significantly differed from the naturalized and introduced species, indicating that established alien species need to be phylogenetically different to become invasive. Positive phylogenetic measures for the invasive aliens across the spatial scales suggested that the presence of invasive aliens could facilitate the establishment of other invasive species. Phylogenetic relatedness was more influenced by temperature than precipitation, especially at a finer spatial scale. With decreased temperature, the invasive species showed a more clustered assemblage, indicating conservatism of their phylogenetic niche. The phylogenetic pattern was different at the family level, although there was a consistent tendency across families to form more clustered assemblages. Discussion Overall, our study showed that the community assemblage became more clustered with the progression of the invasion process. The phylogenetic measures varied at spatial and taxonomic scales, thereby highlighting the importance of assessing phylogenetic patterns at different gradients of the community assembly process.
Swedish tourists’ perceptions, satisfactions and behavioral intentions toward Thailand Destination. A study based on the post-purchase stage

To explore the destination images of Thailand as a tourist destination from the point of view of Swedish Generation X tourists in Vasteras by examining their satisfaction/dissatisfaction and behavioral intentions after traveling to Thailand. To test the theoretical DI formation and interrelationships of those components.A qualitative research approach with in-depth interviews to collect empirical date derived from respondents’ first-hand experiences. Destination Image Theory was used as a background and Content Analysis Approach was used to analyze data. Thailand was perceived positive and negative by Swedish generation X tourists in Vasteras. They were satisfied with their stay at Thailand. After traveling to Thailand, most of them would like to revisit Thailand, but few of them want to travel to new destination. All of them are willing to tell friends or relatives about their experiences in Thailand.
Ancient Plant Lineages Endemic to Africa and Its Islands: An Analysis on the Distribution and Diversity

Although Africa and Madagascar host numerous endemic plant families and genera, there has been no attempt to use recent phylogenies in order to summarise information on their age or map their distribution and diversity. Here, we list 35 plant lineages endemic to Africa and its islands deemed to be older than 100 Mya, map their distribution, richness, and weighted endemism, and discuss intrinsic and extrinsic factors that may have facilitated their survival. High concentrations of ancient endemic lineages are found in the Cape and more broadly across southern Africa, in the Congolian rainforests, but also in East Africa and Madagascar, these last two areas sharing surprisingly many lineages. Africa and its islands host a highly distinctive assemblage of unique plant lineages, adapted to humid, mesic, dry, and in several cases fire-prone, environments. A better understanding of their history and ecology will facilitate their conservation in a changing climate.
Spatio-Temporal Changes in Ecosystem Quality across the Belt and Road Region

The Silk Road Economic Belt and the 21st Century Maritime Silk Road Initiative (BRI) proposed in 2013 by China has greatly accelerated the social and economic development of the countries along the Belt and Road (B&R) region. However, the international community has questioned its impact on the ecological environment and a comprehensive assessment of ecosystem quality changes is lacking. Therefore, this study proposes an objective and automatic method to assess ecosystem quality and analyzes the spatiotemporal changes in the B&R region. First, an ecosystem quality index (EQI) is established by integrating the vegetation status derived from three remote sensing ecological parameters including the leaf area index, fractional vegetation cover and gross primary productivity. Then, the EQI values are automatically categorized into five ecosystem quality levels including excellent, good, moderate, low and poor to illustrate their spatiotemporal changes from the years 2016 to 2020. The results indicate that the spatial distributions of the EQIs across the B&R region exhibited similar patterns in the years 2016 and 2020. The regions with excellent levels accounted for the lowest proportion of less than 12%, while regions with moderate, low and poor levels accounted for more than 68% of the study area. Moreover, based on the EQI pattern analysis between the years 2016 and 2020, the regions with no significant EQI change accounted for up to 99.33% and approximately 0.45% experienced a significantly decreased EQI. Therefore, this study indicates that the ecosystem quality of the B&R region was relatively poor and experienced no significant change in the five years after the implementation of the “Vision and Action to Promote the Joint Construction of the Silk Road Economic Belt and the 21st Century Maritime Silk Road”. This study can provide useful information for decision support on the future ecological environment management and sustainable development of the B&R region.
Employing the Technology Acceptance Model to Explore Moodle’s Online Learning System and Its Effect on Perceived Usefulness and Ease of Use

Moodle is expanding at a very rapid rate when compared to informal in-class transfer. It has a large user base and makes academic content readily available to students on a professional level, particularly in times of crisis like the one the entire world experienced in COVID-19. Professors could still teach during that time, and students could still access academic materials through Moodle's online learning platform using computers or the Moodle application. Moodle has been officially adopted as one of the leading online education systems for lecturers to transfer academic information to students and as a significant medium for students to access academic information due to its success in transferring information quickly and the level of user acceptance.
Protocol for a Pilot Trial to Implement Diagnostics for Clonal Hematopoiesis of Indeterminate Potential into Routine Clinical Care of Older Patients with Breast Cancer

: Clonal hematopoiesis of indeterminate potential (CHIP) refers to the presence of a hematopoietic clone with a common leukemia driver mutation without diagnosis of an underlying hematopoietic disease. The prevalence of CHIP is increasing with age and is associated with pro-inflammatory states, higher risk of cardiovascular diseases (CVD) and therapy-induced leukemia. However, these CHIP-associated risks overlap with treatment-related toxicities of breast cancer therapy, which potentially supports the integration of CHIP into treatment-and survivorship plans. However, so far no data on the feasibility and acceptance of a CHIP-based aftercare are available. In this pilot trial, the feasibility to integrate pre-treatment CHIP diagnostics into the routine care of breast cancer patients is evaluated. Early-stage breast cancer is common among older women and has an excellent long-term outcome. Thus, 80-100 patients with limited stage breast cancer aged ≥ 60 years without known hematological disease will be included. CHIP is assessed by targeted next generation sequencing from peripheral blood samples. The primary outcome measures the estimation of willingness to participate. Secondary outcome measures include evaluation of patient acceptance of the study process, potential fears in relation to CHIP-positivity, and cardiovascular risk profile of CHIP-positive versus CHIP-negative patients.
Natural resources and productivity growth in developing countries

Productivity growth has contributed significantly to boost living standards in many regions of the world. Concerns about certain emerging nations’ dependence on unprocessed natural resource exports have led some analysts to be sceptical about the possibilities for structural reform in resource-rich countries. We hope to contribute to the research on the nexus between natural resources and growth by examining the impact of the dependence on resources on TFP growth in 91 developing countries from 1980 to 2019. Findings demonstrate unequivocally that TFP growth is lower in resource-rich emerging nations. The results are robust to several tests, including additional control variables and the partition of resource reliance between point-source and diffuse-source resources. Furthermore, the establishment and maintenance of democratic and economic institutions enable resource-rich countries to avoid the curse.
Obstacle Avoidance Path Planning for Apple Picking Robotic Arm Incorporating Artificial Potential Field and A* Algorithm

With the development and maturity of the automated robotics industry, more and more apple plantations are introducing automated picking robotic arms for fruit picking. However, the complex environment in which apple fruit is picked has made it an urgent problem to optimise the robot’s picking performance through obstacle avoidance path planning. The experiment selects the Six degrees of freedom manipulator as the research object, and on the basis of its Kinematics analysis, introduces the introduction of artificial potential field (APF) to carry out the path planning of the manipulator. At the same time, it integrates it with A* algorithm to jointly achieve the optimization of the parameters of the obstacle avoidance path of the manipulator. In addition, in order to avoid parameter optimization falling into local extremum during the path planning process, the IRRT algorithm is incorporated to re plan the path, improve the smoothness of the path, and finally verify its obstacle avoidance effect through simulation experiments. The results showed that in the convergence comparison, the research method had the minimum loss function value and the stable fitness value as soon as the iteration proceeded to the 50th and 20th generation, respectively. A On the dataset, the research method had the minimum MAPE value when the iteration proceeded to the 45th generation, with a value close to 0. At the same moment, the MAPE values of the IAPF algorithm, the IRRT algorithm and the literature were 0.052%, 0.108% and 0.218%, respectively. In the practical application analysis, when the robot arm starts running in three different starting positions a, b and c, the IRRT algorithm’s obstacle avoidance path has a larger arc and tends to reach the target location through a longer path, while the research method tends to find a relatively closer obstacle avoidance path that can be passed smoothly. The above results show that the research method is highly adaptable to robotic arm path avoidance planning and can complete obstacle avoidance path planning faster and more reasonably, providing new technical support for optimising the path planning system of apple picking robots.
The Incidence and Risk Factors of Acute Myocardial Infarction Among Patients with Gastrointestinal bleeding: A Retrospective Study

Purpose Patients with gastrointestinal bleeding (GIB) and acute myocardial infarction (AMI) have higher mortality than that with either GIB or AMI alone. The aims of this study were to determine the incidence and risk factors of AMI in patients with GIB. Patients and Methods From January 2015 to January 2018, we retrospectively studied 1287 patients with GIB in Renmin Hospital of Wuhan University. Various demographic, laboratory and outcome data were reviewed by charts. Results Thirty-seven patients had AMI and were placed in AMI group and the rest 1250 patients were in non-AMI group. Patients with AMI were more likely to be older than 70 years, have hypertension, coronary heart disease, chronic kidney disease, and have the recent history of taking aspirin before admission. The ROC curve of hemoglobin (HB) on admission showed area under curve was 0.762, the optimal cut-off value is 76.5g/L. Logistic regression analysis showed that age ≥ 70 years old, coronary heart disease and HB < 76.5g/L on admission were independent risk factors of AMI in patients with GIB. The mortality of patients during hospitalization in AMI group and in non-AMI group were 45.95% and 5.48%, respectively. Patients who displayed a history of liver disease and HB < 76.5g/L on admission had a higher death rate. Conclusion GIB increased the risk of subsequent AMI, especially in patients over 70 years old, with history of coronary heart disease and HB < 76.5g/L on admission. Patients with GIB and AMI who had history of liver disease and HB < 76.5g/L on admission had a higher mortality rate. Clinicians should identify the high-risk patients of AMI among the GIB population early and prevent AMI.
Applying Natural Language Processing to Textual Data From Clinical Data Warehouses: Systematic Review

Background In recent years, health data collected during the clinical care process have been often repurposed for secondary use through clinical data warehouses (CDWs), which interconnect disparate data from different sources. A large amount of information of high clinical value is stored in unstructured text format. Natural language processing (NLP), which implements algorithms that can operate on massive unstructured textual data, has the potential to structure the data and make clinical information more accessible. Objective The aim of this review was to provide an overview of studies applying NLP to textual data from CDWs. It focuses on identifying the (1) NLP tasks applied to data from CDWs and (2) NLP methods used to tackle these tasks. Methods This review was performed according to the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. We searched for relevant articles in 3 bibliographic databases: PubMed, Google Scholar, and ACL Anthology. We reviewed the titles and abstracts and included articles according to the following inclusion criteria: (1) focus on NLP applied to textual data from CDWs, (2) articles published between 1995 and 2021, and (3) written in English. Results We identified 1353 articles, of which 194 (14.34%) met the inclusion criteria. Among all identified NLP tasks in the included papers, information extraction from clinical text (112/194, 57.7%) and the identification of patients (51/194, 26.3%) were the most frequent tasks. To address the various tasks, symbolic methods were the most common NLP methods (124/232, 53.4%), showing that some tasks can be partially achieved with classical NLP techniques, such as regular expressions or pattern matching that exploit specialized lexica, such as drug lists and terminologies. Machine learning (70/232, 30.2%) and deep learning (38/232, 16.4%) have been increasingly used in recent years, including the most recent approaches based on transformers. NLP methods were mostly applied to English language data (153/194, 78.9%). Conclusions CDWs are central to the secondary use of clinical texts for research purposes. Although the use of NLP on data from CDWs is growing, there remain challenges in this field, especially with regard to languages other than English. Clinical NLP is an effective strategy for accessing, extracting, and transforming data from CDWs. Information retrieved with NLP can assist in clinical research and have an impact on clinical practice.
Numerical Simulation on Thickness Dependency and Bias Stress Test of Ultrathin IGZO Thin‐Film Transistors Via a Solution Process

The authors report the effect of ultra‐thin channel layer thickness on the performance of an amorphous InGaZnO (a‐IGZO) thin‐film transistor (TFT). Numerical simulation is used to investigate the thickness effect on the a‐IGZO TFT output parameters. The simulation results are compared to measurements of the stability of nitrate ligand‐based hexaaqua complexes solution‐processed ultrathin a‐IGZO transistors a‐IGZO. This TFT is also tested under negative illumination bias stress (NIBS) and positive bias stress (PBS). The thinner channel layer is found to have a better performance than the thicker channel layer. The 4 nm‐thick, ultra‐thin a‐IGZO TFT exhibits high saturation mobility (7.56 cm2 V−1 s−1), low threshold voltage (2.73 V), a small value of sub threshold swing (0.22 V dec−1), and a high on/off ratio ( 1.77×108 ). It is also noticed that the threshold voltage (Vth) shifts negatively as the thickness increases. The 4 nm long channel TFT shows more stability under NIBS and PBS while 16 nm have a strong degradation under NIBS and PBS.