Miracle-dz/UniFAR-FTUs huggingface dataset:
Adaptive cooperation control of wind power generation systems based on Hamilton system under limited input

Numerous wind turbines form large‐scale wind farms, which are complex nonlinear systems with uncertain parameters. The issue of maximum wind energy capture and coordinated control has always been a research hotspot. In this article, under the condition of limited input and uncertain parameters, the preset controller and the adaptive cooperation control are designed to realize the maximum wind energy capture for every wind turbine and the adaptive cooperation control of multiple wind turbines. The research gap lies in that the Hamilton model of wind power generation system is established with uncertain parameters, and the preset controller (method) is designed to capture the maximum wind energy. Under the hypothesis that the uncertain part can be expressed as a linear form about unknown parameter, and using the saturation function processing method in the diagonal matrix, an adaptive feedback controller with limited input is designed to realize the adaptive cooperation control of multiple wind turbines. The simulation results show that under the conditions such as variable wind speed, limited input and uncertain parameters, the wind turbine remain normal operation at the desired angular velocity. It can be concluded that not only the maximum wind energy capture is realized under the condition of variable wind speed, in which the wind turbine can operate on the optimal power curve to improve the utilization of wind energy, but also the adaptive cooperation control of multiple wind turbines can be achieved with limited input and parameter perturbation.
Sporotrichosis in Older Adults: A Cohort Study of 911 Patients from a Hyperendemic Area of Zoonotic Transmission in Rio de Janeiro, Brazil

Generally, older people tend to suffer from more severe infections than younger adults. In addition, there are accumulations of comorbidities and immune senescence in some cases. This cohort study evaluated the clinical and epidemiological characteristics of older adults (≥60 years old) with sporotrichosis. The cohort consisted of 911 patients with a median age of 67 years, most of whom were female (72.6%), white (62.1%), and afflicted with comorbidities (64.5%). The lymphocutaneous form occurred in 62% of the patients, followed by the fixed form (25.7%), cutaneous disseminated form (8.9%), and extracutaneous/disseminated forms (3.3%). In this study, we draw attention to the frequency of osteoarticular involvement (2.1%) secondary to skin lesions such as osteomyelitis and/or tenosynovitis. A clinical cure was achieved in 87.3% of cases. Itraconazole was used in 81.1% of cases, while terbinafine was used in 22.7% of cases, usually in low doses. Survival analysis showed that the median treatment time was 119 days, and the multiple Cox model demonstrated that the presentation of a black coloration and diabetes was associated with a longer treatment time required to establish a cure. Therefore, these subgroups should be monitored more closely to reduce possible difficulties during treatment. It would be interesting to conduct more studies analyzing older adults with sporotrichosis from different geographic areas to better comprehend the disease in this group.
Near zone radar imaging and feature capture of building interiors

As the target of detection becomes more and more complex in nature, the challenge in radar technology and signal processing capability deepens accordingly. Due to the increasing importance on homeland security and urban counter-terrorism, throughwall radar imaging has become a hot research topic in recent times. The signal attenuation and distortion through the wall is quite significant which can lead to false interior imagery. This thesis is developed to study and demonstrate the capability of EM and signal processing for through-wall building imaging and feature identification. The imaging algorithm employed here has a model-based filtering function built up on top of the conventional FFT method to extract specific features. The theoretical background of using a high frequency EM technique in modeling building scattering is discussed thoroughly. Upon validating with RCS measurement of a building target, the NEC-BSC ray-tracing code is used to study feature capturing, polarization effect, bistatic synthetic aperture radar (SAR), and the through-wall image improvement techniques. An innovative feature identification method has been proposed based largely on the scattering mechanisms of the building features. In addition, it is shown how polarization and bistatic SAR is useful in detecting or avoiding certain building features and hidden objects. Finally, the CLEAN algorithm with a pre-computed wall model is employed to remove exterior wall returns, which leads to better image of the building interiors. ii Dedicated to my family
Solution to the motion of a delta manipulator with three degrees of freedom

ABSTRACT Based on the mechanical structure of a Delta manipulator with three degrees of freedom, the kinematic characteristics of the parallel manipulator were analyzed, and the vector relation between the static and moving platforms was given. The inverse kinematic function of the three-degree-of-freedom (3-DOF)parallel manipulator was deduced by the vector equation. The simulated forward kinematic solution in the moving platform was carried out by Pro/E modeling software and virtual prototype simulation software ADAMS, which is proved simple. These research contents provide a valuable reference for the adjustment and operation of 3-DOF Delta manipulator prototypes with respect to its dynamic performance, motion track planning, mechanical structure, system control, etc.
Sentiment Analysis and Classification of Forest Fires in Indonesia

so the preprocessing process must be carried out as was done in research [5], which retrieved Twitter data on the theme of COVID 2019. Moreover, weighting must be applied to tasks that must be completed prior to classification. This study uses VADER or commonly known as the lexicon. [6] It uses a lexicon that combines lexical dictionary features as a polarity assessment. Sentiment scores of 5 additional criteria, namely exclamation marks, large alphabet, level of word order, polarity shift due to the term "but," and using the tri-gram feature to study negation [7]. Once the text has been labeled, we will classify it using the sentiment analysis. The Nave Bayes technique, Random Forest, and SVM are some reliable classifications that have been demonstrated in numerous research (Support Vector Machine). A popular algorithm that is frequently employed by researchers is Naïve Bayes. The following researchers have used the Naive Bayes method for sentiment analysis research: : [8] analyzing the online store JD.ID, [9] regarding awareness of procedures to prevent COVID 2019. Random Forest is rarely implemented in research on sentiment analysis, although it has recently been investigated to gauge its accuracy. It is used by a number of researchers, including [10], who achieves an accuracy of about 0.829. Moreover, the SVM (Support Vector Machine) approach, whose accuracy is 85%, is also being investigated in sentiment analysis study by [11]. Hence, researchers want to compare the values of the 3 methods namely Naïve Bayes, Random Forest and SVM (Support Vector Machine) to find out the difference in accuracy of the three when using the same data. As for the accuracy will be calculated using the calculation on the confusion matrix. In addition, the researcher also wants to compare the results of classifying sentiment statements which are divided into positive, negative and neutral sentiments.
The Role of FAS Receptor Methylation in Osteosarcoma Metastasis

Osteosarcoma is the most frequent primary malignant bone tumor with an annual incidence of about 400 cases in the United States. Osteosarcoma primarily metastasizes to the lungs, where FAS ligand (FASL) is constitutively expressed. The interaction of FASL and its cell surface receptor, FAS, triggers apoptosis in normal cells; however, this function is altered in cancer cells. DNA methylation has previously been explored as a mechanism for altering FAS expression, but no variability was identified in the CpG island (CGI) overlapping the promoter. Analysis of an expanded region, including CGI shores and shelves, revealed high variability in the methylation of certain CpG sites that correlated significantly with FAS mRNA expression in a negative manner. Bisulfite sequencing revealed additional CpG sites, which were highly methylated in the metastatic LM7 cell line but unmethylated in its parental non-metastatic SaOS-2 cell line. Treatment with the demethylating agent, 5-azacytidine, resulted in a loss of methylation in CpG sites located within the FAS promoter and restored FAS protein expression in LM7 cells, resulting in reduced migration. Orthotopic implantation of 5-azacytidine treated LM7 cells into severe combined immunodeficient mice led to decreased lung metastases. These results suggest that DNA methylation of CGI shore sites may regulate FAS expression and constitute a potential target for osteosarcoma therapy, utilizing demethylating agents currently approved for the treatment of other cancers.
Generating game immersion features for immersive game selection

The immersion is an essential component of the modern digital game. Currently, immersion is the required component which should be included in the digital game. The modern game which success within game industry surely has included immersion as a component. Although digital games have been introduced for many years, yet what is immersion game been known very little. Regarding the intensive study about user immersion, there is still a lack of knowledge about game immersion. First, the game designers, game developers, and gamers are facing problems how to understand whether their game is immersive or not. There is no knowledge regarding how to evaluate their game, whether immersive or not, and this process requires expert knowledge. Second, currently, the game designers are relied on speculative interpretation to evaluate their game because there is no method to examine whether the game is immersive or not. Therefore, this study aims to propose a method that enable to evaluate if the game is immersive or not. This method is emerged as knowledge and recommendation that quickly be able to assist the game designers, game developers, and gamers evaluating whether a game is immersive or not. First, this research conducts a literature review to categorize the game immersion features. Second, this study proposes an effective method that can analyse and recommends whether a game is immersive or not. Finally, this study reveals that the finding could be used as a recommendation for the other immersive technology platforms.
Building blocks for a leading edge high‐order flow solver

An important trend in Computational Fluid Dynamics is towards high‐order methods, as they offer a substantially lower discretization error for the same number of degrees of freedom (DOF). Examples are the Spectral‐Element Methods (SEM) and Discontinuous Galerkin (DG) methods. Unfortunately, with most implementations the work load of such solvers increases drastically with the number of DOF, for example, when increasing the polynomial degree of the approximation. This issue gets particular pressing for elliptic solvers which are a vital building block in the time‐stepping of the incompressible Navier‐Stokes equations, resulting from pressure projection methods or implicit treatment of viscous terms. So far, this drastic increase of resources has hampered the use of SEM for higher polynomial degrees, such as 16 or more.
Factors Associated with Depression, Anxiety, and Somatic Symptoms among International Salespeople in the Medical Device Industry: A Cross-Sectional Study in China

Background: The physical and mental health of corporate employees is equally important, especially for international salespeople in the in vitro diagnostic (IVD) medical device industry. The rapid growth of the IVD market is driven by the increasing prevalence of chronic and infectious diseases. This study aims to determine the prevalence of depression, anxiety, and somatic symptoms among international salespeople in China’s IVD industry and identify the association of socio-demographic, occupational, organizational, and psychosocial factors with mental health outcomes for depression, anxiety, and somatic symptoms in Chinese IVD international salespeople. Methods: The study was a cross-sectional survey of international salespeople (ISs) in IVD companies officially registered in China. An online survey was designed to collect data through email contact with IVD companies and social media between August 2022 and March 2023. Measured factors included effort-reward imbalance (ERI), health-promoting leadership (HPL), health climate (HC), inner strength (IS), and perceived social support (PSS). Mental health outcomes assessed using the Core Symptom Index (CSI) were depression, anxiety, and somatic symptoms. Results: A total of 244 salespeople responded to the survey. CSI scores indicated that 18.4% (n = 45) and 10.2% (n = 25) of the respondents had symptoms of major depression and anxiety, respectively. ERI was positively correlated, while the IS and PSS were negatively correlated with major depression, anxiety, and somatic symptoms (p < 0.01). The health climate was negatively correlated with major depression (p < 0.05). Education background was associated with somatic symptoms (p < 0.05). ERI, IS, and gender were significant predictors of major depression, anxiety, and somatic symptoms (p < 0.05). Conclusion: The prevalence of depression and anxiety in China’s IVD international salespeople was considered low compared with the prevalence in Chinese populations during COVID-19 but higher than those before the pandemic. Effort–reward imbalance, inner strength, and gender were significant factors in major depression, anxiety, and somatic symptoms among IVD international salespeople.
Simple numerical calculation method of flow velocity on roof of train running in tunnel

A pantograph mounted on a high-speed train roof is exposed to high-speed air flow while traveling, and lift force is generated in the pantograph. To ensure high current collecting performance of the pantograph, it is important to appropriately adjust the lift force generated in the pantograph. The flow velocity along the roof of a train has a significant influence on the lift force. In this study, we proposed a simple calculation method that enabled us to easily calculate the flow on the train roof in a tunnel using a personal computer. To validate the effectiveness of the proposed method, model experiments were carried out and calculation and experimental results were compared. Furthermore, the influence of hydraulic friction coefficients on train roof flow velocity was examined using the proposed method, which was not time consuming.
Uma Abordagem de Encadeamento de Serviços para Virtualização de Funções de Rede em uma Arquitetura de Computação em Borda

A Internet das Coisas e a Computação em Borda têm sido amplamente utilizadas, permitindo a criação de diversas aplicações e fornecendo serviços que habilitam a interconexão entre o mundo físico e o virtual. Essas tecnologias necessitam de hardware para armazenamento de dados e execução dos serviços. O paradigma de virtualização de recursos de rede surge como solução para esse desafio. Nesse contexto, este trabalho propõe uma abordagem de gerenciamento e orquestração de funções de rede e encadeamento de serviços visando diminuir a sobrecarga da rede. Baseado nos experimentos realizados, o uso de CPU dos nós que fornecem os serviços obteve um máximo de 72.88% e o consumo máximo de memória foi de 68.13%.
Analysis of Dielectric Prebreakdown of High-k Stacking Polycrystalline MIM by Stochastic Trap-Clusters Growing and Percolation-Based Transportation

We propose a method to analyze the dielectric prebreakdown (DB) which is based on: 1) charge transport; 2) stochastic trap-cluster generations; and 3) percolation in a metal–insulator–metal (MIM) stacked polycrystalline high- ${k}$ capacitor of TiN–TiO2–ZrO2–TiO2–TiN. We assume that measured dielectric leakage current until the breakdown is comprised of transient transports under static fields: direct tunneling, trap-assisted tunneling (TAT), and inelastic tunneling. The charge transports induce trap generation and formation of stochastic trap-cluster. The generated trap-cluster amplified the stress-induced leakage current (SILC). One of the clusters can be expanded and electrically link the cathode and anode throughout the dielectric to form a critical path. We can model the current through this path analytically by partition function and percolation. By careful analysis of measured time-dependent dielectric leakage currents, we found that prebreakdown is most related to SILC and inelastic tunneling at a low electric field (< 4 MV/cm).
Antioxidant Compounds and Health Benefits of Citrus Fruits

Recent evidence emanating from epidemiological prospective studies shows that increased intakes of antioxidant-rich fruits, vegetables, and legumes are associated with a lower risk of developing chronic oxidative stress-related diseases like cardiovascular diseases and cancer, as well as with a lower risk of cardiovascular, cancer, and all-cause mortality rates [. ].
A Novel and Low-cost Approach for Intravitreal Injection in an Experimental Model of Endophthalmitis

Abstract Purpose Animal models are necessary in understanding the pathogenesis of endophthalmitis and are also necessary to assist the development of new therapeutics for this sight-threatening ocular inflammation. Hamilton syringes are usually preferred to inject pathogens when performing experiments on test subjects, however, this method has technical and financial disadvantages. In this study, we report the findings and assess the related benefits of applying a novel low-cost intravitreal injection technique to initiate endophthalmitis in a mouse model while using the Eppendorf tip and a 26G needle. Methods The 18-hr culture of clinical isolates of bacteria (Staphylococcus aureus and Pseudomonas aeruginosa) and fungus (Aspergillus flavus and Candida albicans) were resuspended to a final concentration of 10,000 colony forming units (CFU)/1 µL which were separately injected intravitreally into C57BL/6 mice (6–8 weeks) using a 0.1–2. 5µL pipette attached to the modified Eppendorf tip with a 26G needle. The contralateral eye served as vehicle/uninjected control. Disease progression was determined by assessing the corneal haze, opacity, bacterial burden, and retinal histology of the eyes used in the model. Following euthanization, bacteria-infected mice were enucleated after 24 hr of the initial injection, and fungus-infected mice after 72 hr. Results Of the 50 mice injected, the modified technique was successful in 48 mice. Two mice were excluded due to cataract formed by accidental injury to the lens. The experimental endophthalmitis mice model successfully mimicked the natural clinical course. Clinical assessment and histopathology confirmed the influx of inflammatory cells into the posterior segment of the eye along with dissolution of retinal architecture. Conclusion Our novel method of injection using a modified Eppendorf tip and 26G needle yielded a cost-effective mouse model of clinical endophthalmitis, resulting in reproducible infection for understanding various aspects of its pathobiology.
Vortex ring and rotor wake interaction with solid surfaces

The interaction between vortex structures and solid surfaces represents an inherently complex flow environment. When considering the rotor wake downwash generated by rotary-wing aircraft operating in close proximity to the ground, a phenomenon known as brownout can occur. Brownout is characterised by the entrainment of small ground particles by the rotor wake and when conditions are fully developed, cockpit visibility can be wholly obscured by the dust particles entrained by the rotor wake. In such instances aircrew can rapidly lose situational awareness, significantly increasing the probability of a mishap. Brownout dust cloud characteristics are highly variable, however the development of a very large cloud does not automatically equate to an unacceptable degradation in aircrew situational awareness. In some instances the region of clear air close to the fuselage is maintained throughout landing, despite development of a large cloud beyond the periphery of the rotor disk. Such flow structures are colloquially referred to as "dust donuts", as when viewed from above they have the appearance of a toroid. Although the wake generated by rotary wing vehicles has been extensively studied, the mechanisms that underlie the development of "dust donuts" are not well understood. The focus of this dissertation is an investigation of the fundamental flow behaviour that potentially yields large-scale toroid flow structures, to enable a more thorough understanding of the phenomenon. The first part of the study implemented a numerical model to assess the interaction between vortex rings and solid surfaces. The vortex-wall interaction was used to investigate the tendency of the flow towards recirculatory behaviour, and to look at the flow pattern generated near the wall for both wall-normal and oblique impacts. It was found that the global flow field recirculation pattern consistent with a large-scale toroid structure was only evident for a wall-normal impact, but that in all test cases the near-wall flow structures generated by vortex ring / wall interactions were congruous with flow patterns required for particle uplift. This dissertation then experimentally examines the hypothesis that a large-scale "global recirculation" flow structure exists and perpetuates a toroidal flow structure. Compared to the numerical study, the experiments more closely replicated conditions associated with full-scale operations; most notably the generation of a helical rotor downwash, which enabled direct
Novel application of a process convolution approach for calibrating output from numerical models

Output from numerical models at high spatial and temporal resolutions is critical for modeling applications in a variety of disciplines. Prior to its use in modeling, output from climate models must be brought to a finer spatial resolution and calibrated with respect to observations. The calibration of model output, referred to as bias‐correction, poses many statistical challenges. Here, we develop a bias‐correction method in which systematic biases in the mean and standard deviation of model output are corrected. In addition, we employ a novel process convolution approach to correct bias in temporal dependence. We apply this approach to temperature simulations generated by a regional climate model over the Northeastern USA. The goal of this study was to correct systematic bias in model simulations over historical (1976–2005) and future (2006–2099) time periods while simultaneously preserving future trends resulting from carbon emissions scenarios. We compare the proposed method to a quantile mapping method (empirical quantile mapping, EQM). The proposed method resulted in a more effective correction of seasonal biases and temporal dependence compared to EQM.