Miracle-dz/UniFAR-FTUs huggingface dataset:
Mathematical Model and PI Controller Design Based on Indirect Vector Control for Permanent Magnet Synchronous Motor

A mathematical model of a permanent magnet synchronous motor (PMSM) is necessary to design the control of PMSM drives. The mathematical model of a three-phase system is not commonly used for control design since this approach is a time-varying model. As a result, control strategy design becomes even more difficult. Due to this problem, this paper presents a dynamic model of the PMSM using the dq modeling method. The dynamic model derived in this work has been validated with the exact topology model in the MATLAB/Simulink program. In addition, this model is applied to designing the indirect vector control for a PMSM drive. The speed and the current control loops based on the PI controller are considered. The simplified design approach for the PMSM drives is presented in this paper. The simulation results show that the proposed controller design can accurately regulate the actual speed obeying the command speed. The speed accuracy is up to 99.97% in the load torque changes and 99.98% in the command speed changes.
Kernel-Windowed SDFT Based Frequency-Locked Loop for Capacitance Sensing on an FPGA

Sliding discrete Fourier transform with kernel windowing technique is proposed for frequency estimation of periodic signals that can be applied to capacitance sensing. SDFT is an efficient technique to compute ${N}$ -point DFT of a signal by sliding the rectangular window one sample at a time. In the proposed work Hanning and Blackman windows replace rectangular window of SDFT to reduce the spectral leakage and increase the mainlobe width of the spectra. The concept of increased mainlobe width of the SDFT spectra has been exploited to increase the operating range of the frequency-locked loop. Kernels of these windows have been computed with certain coefficients and incorporated in the FLL to increase the operating range which increases the estimation input signal frequency. Designed FLL with Hanning window having bin index ${k} = 1$ estimates frequency from 4 to 56 kHz while with Blackman window estimates frequency from 6 to 75 kHz. The proposed scheme with kernel windowing has been implemented in FPGA and verified for enhanced performance. The experimental investigation on the proposed technique is validated for discrete capacitance sensing with maximum frequency estimation error of 0.054 and liquid level measurement of 0 - 13.5 cm with a sensitivity of 4.435 pF/mm. This method provides wide range of frequency estimation which results in wide range of capacitance measurement.
Robust tracking for nanopositioning stages using sliding mode control with active disturbance rejection: Design and implementation

This paper presents the design and implementation of a novel sliding mode control integrated with active disturbance rejection (SMCDR) for precise robust trajectory tracking of piezoelectric nanopositioning stages. The model uncertainties, nonlinearity, and external disturbances of the piezoelectric nanopositioning stage are regarded as a lumped disturbance, which is estimated by an extended state observer. The active disturbance rejection control (ADRC) strategy is used to realize a preliminary trajectory tracking, while the sliding mode control is adopted to handle the estimation error and residual uncertainties, and to improve the tracking performance. The exponential stability of the proposed SMCDR is proved using Lyapunov’s direct method. The proposed SMCDR controller combines the strength of both ADRC and sliding mode control, exhibits a simple structure, requires only the position measurements, and does not require any information of model parameters except for an approximate constant gain. Experimental results reveal the robustness of the SMCDR approach in suppressing the hysteresis of piezoelectric actuator, and illustrate the superior performance over conventional ADRC, integral sliding mode controller (ISMC) and PID controller for trajectory tracking control of piezoelectric nanopositioning stages.
Assessment of Orbital Compartment Pressure: A Comprehensive Review

The orbit is a closed compartment defined by the orbital bones and the orbital septum. Some diseases of the orbit and the optic nerve are associated with an increased orbital compartment pressure (OCP), e.g., retrobulbar hemorrhage or thyroid eye disease. Our aim was to review the literature on the different approaches to assess OCP. Historically, an assessment of the tissue resistance provoked by the retropulsion of the eye bulb was the method of choice for estimating OCP, either by digital palpation or with specifically designed devices. We found a total of 20 articles reporting direct OCP measurement in animals, cadavers and humans. In nine studies, OCP was directly measured in humans, of which five used a minimally invasive approach. Two groups used experimental/custom devices, whilst the others applied commercially available devices commonly used for monitoring the compartment syndromes of the limbs. None of the nine articles on direct OCP measurements in humans reported complications. Today, OCP is mainly estimated using clinical findings considered surrogates, e.g., elevated intraocular pressure or proptosis. These diagnostic markers appear to reliably indicate elevated OCP. However, particularly minimally invasive approaches show promises for direct OCP measurements. In the future, more sophisticated, specifically designed equipment might allow for even better and safer measurements and hence facilitate the diagnosis and monitoring of orbital diseases.
Fault diagnosis of industrial robot gearbox using joint interclass and intraclass mappings

Due to complex structure and harsh operating conditions, it remains challenging to accurately diagnose industrial robot gearbox fault patterns. For this reason, a joint interclass and intraclass mappings (JIIM) strategy is presented in this paper to enhance the performance of industrial robot gearbox fault diagnosis. To this end, an echo state network (ESN) is first adopted to map the training data into their class centers for minimizing the interclass distance. Meanwhile, the maximization of interclass distance in the data space is achieved by equalizing the distance between class centers. For the mapped data, another ESN is proposed to classify the fault patterns. The proposed JIIM method is evaluated by fault-diagnosis experiments for industrial robot gearboxes. Improvements owing to minimizing the intraclass distance and equalizing the interclass distance are discussed in detail. Results show that the presented JIIM can efficiently improve the performance of industrial robot gearbox fault diagnosis.
A Combination of Metabolomics and Machine Learning Results in the Identification of a New Cyst Nematode Hatching Factor

Potato Cyst Nematodes (PCNs) are an economically important pest for potato growers. A crucial event in the life cycle of the nematode is hatching, after which the juvenile will move toward the host root and infect it. The hatching of PCNs is induced by known and unknown compounds in the root exudates of host plant species, called hatching factors (HFs, induce hatching independently), such as solanoeclepin A (solA), or hatching stimulants (HSs, enhance hatching activity of HFs). Unraveling the identity of unknown HSs and HFs and their natural variation is important for the selection of cultivars that produce low amounts of HFs and HSs, thus contributing to more sustainable agriculture. In this study, we used a new approach aimed at the identification of new HFs and HSs for PCNs in potato. Hereto, root exudates of a series of different potato cultivars were analyzed for their PCN hatch-inducing activity and their solA content. The exudates were also analyzed using untargeted metabolomics, and subsequently the data were integrated using machine learning, specifically random forest feature selection, and Pearson’s correlation testing. As expected, solA highly correlates with hatching. Furthermore, this resulted in the discovery of a number of metabolite features present in the root exudate that correlate with hatching and solA content, and one of these is a compound of m/z 526.18 that predicts hatching even better than solA with both data methods. This compound’s involvement in hatch stimulation was confirmed by the fractionation of three representative root exudates and hatching assays with the resulting fractions. Moreover, the compound shares mass fragmentation similarity with solA, and we therefore assume it has a similar structure. With this work, we show that potato likely produces a solA analogue, and we contribute to unraveling the hatch-inducing cocktail exuded by plant roots.
Bioinformatics Analysis Highlights Five Differentially Expressed Genes as Prognostic Biomarkers of Cervical Cancer and Novel Option for Anticancer Treatment

Cervical cancer is one of the most common gynecological malignancies and is related to human papillomavirus (HPV) infection, especially high-risk type HPV16 and HPV18. Aberrantly expressed genes are involved in the development of cervical cancer, which set a genetic basis for patient prognosis. In this study, we identified a set of aberrantly expressed key genes from The Cancer Genome Atlas (TCGA) database, which could be used to accurately predict the survival rate of patients with cervical squamous cell carcinoma (CESC). A total of 3,570 genes that are differentially expressed between normal and cancerous samples were analyzed by the algorithm of weighted gene co-expression network analysis (WGCNA): 1,606 differentially expressed genes (DEGs) were upregulated, while 1,964 DEGs were downregulated. Analysis of these DEGs divided them into 7 modules including 76 hub genes. Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) enrichment analysis revealed a significant increase of genes related to cell cycle, DNA replication, p53 signaling pathway, cGMP-PKG signaling pathway, and Fanconi anemia (FA) pathway in CESC. These biological activities are previously reported to associate with cervical cancer or/and HPV infection. Finally, we highlighted 5 key genes (EMEMP2, GIMAP4, DYNC2I2, FGF13-AS1, and GIMAP1) as robust prognostic markers to predict patient’s survival rate (p = 3.706e-05) through univariate and multivariate regression analyses. Thus, our study provides a novel option to set up several biomarkers for cervical cancer prognosis and anticancer drug targets.
Serious games may shape the future of accounting education by exploring hybrid skills

ABSTRACT New technologies shape the market by requiring hybrid skills for accounting professionals. Serious games may help to prepare students by cultivating these skills. However, an improper game application may disrupt students’ skill development. A guide is necessary to avoid a disruptive scenario by making serious games a proper teaching methodology to ensure desired learning outcomes. Thus, this research aims to structure a valid holistic framework by integrating game-based learning, the theory of planned behavior, and experiential learning theory to potentialize the benefits of games and minimize their risks. The objective was achieved by designing a framework proposal and validating it with arguments from modern validation theory. This research shows the benefits of serious games and contributes to the accounting education field by adding a new validated framework that guides educators to explore the development of students’ hybrid skills.
A Novel Extracellular Matrix Gene-Based Prognostic Model to Predict Overall Survive in Patients With Glioblastoma

Background: Glioblastoma (GBM), one of the most prevalent brain tumor types, is correlated with an extremely poor prognosis. The extracellular matrix (ECM) genes could activate many crucial pathways that facilitate tumor development. This study aims to provide online models to predict GBM survival by ECM genes. Methods: The associations of ECM genes with the prognosis of GBM were analyzed, and the significant prognosis-related genes were used to develop the ECM index in the CGGA dataset. Furthermore, the ECM index was then validated on three datasets, namely, GSE16011, TCGA-GBM, and GSE83300. The prognosis difference, differentially expressed genes, and potential drugs were obtained. Multiple machine learning methods were selected to construct the model to predict the survival status of GBM patients at 6, 12, 18, 24, 30, and 36 months after diagnosis. Results: Five ECM gene signatures (AEBP1, F3, FLNC, IGFBP2, and LDHA) were recognized to be associated with the prognosis. GBM patients were divided into high– and low–ECM index groups with significantly different overall survival rates in four datasets. High–ECM index patients exhibited a worse prognosis than low–ECM index patients. Four small molecules (podophyllotoxin, lasalocid, MG-262, and nystatin) that might reduce GBM development were predicted by the Cmap dataset. In the independent dataset (GSE83300), the maximum values of prediction accuracy at 6, 12, 18, 24, 30, and 36 months were 0.878, 0.769, 0.748, 0.720, 0.705, and 0.868, respectively. These machine learning models were provided on a publicly accessible, open-source website (https://ospg.shinyapps.io/OSPG/). Conclusion: In summary, our findings indicated that ECM genes were prognostic indicators for patient survival. This study provided an online server for the prediction of survival curves of GBM patients.
Consumption of Yoghurt and Other Dairy Products and Risk of Colorectal Cancer in Iran: The IROPICAN Study

Background: There is evidence of an inverse association between yoghurt intake and risk of colorectal cancer (CRC). We aimed at investigating the association between the intake of yoghurt and other dairy foods consumed in Iran and CRC risk. Methods: Our analysis included 4070 subjects within the IROPICAN (Iran Study of Opium and Cancer) study. Detailed information was collected by the use of validated questionnaires. We estimated adjusted odds ratios (OR) and 95% confidence intervals (CI) for the association between the intake of total dairy products, and, separately, of yoghurt, milk, cheese, kashk, dough, cream, ice cream, and other milk products, and CRC using unconditional logistic regression analyses. The intake was categorized in tertiles. Results: Overall, we analyzed 865 cases and 3205 controls. Total dairy products intake was not associated with CRC. The OR for one tertile increase (OR_T) in yoghurt intake was 0.97 (95% CI 0.87–1.08) for CRC and 0.66 (95% CI 0.52–0.84) for proximal colon cancer. Cream intake was associated with CRC (OR_T3 = 1.33, 95% CI 1.08–1.64), colon (OR_T3 = 1.37, 95% CI 1.03–1.81), and proximal cancer (OR_T3 = 1.29, 95% CI 1.04–1.61). The OR of distal colon cancer for ice cream intake was 0.59 (95% CI 0.43–0.82). Other dairy products were not associated with CRC risk.
Mathematical models of control by the interconnected mechanical and thermal processes in nonlinear dynamic systems disturbed by temperature effects

The opportunity of control by the interconnected mechanical and thermal processes in nonlinear disturbed dynamic systems is proved, both at their irregular movements, and at parametrical temperature indignations. Conditions on parameters of systems and the control providing stability of stationary points are received. It is shown, that it is possible to provide a regularity of chaotic fluctuations and is also possible to provide a control of fluctuations when take place parametrical temperature disturbances by a choice of parameters of the connected thermal and mechanical subsystems. For control by the interconnected mechanical and thermal processes it is necessary to include into feedback of a mechanical subsystem a signal proportional to temperature difference. The quantitative estimations confirming the qualitative analysis of constructed mathematical models are received. Use of interrelation of thermal and mechanical energy for control by movement and temperature fields in mechanical dynamic systems with sources of heat is essential and modern [1] problem. For example, this problem is important for perspective micromechanical gyroscopic sensors and sensors of other physical values, of gradiometers or for macromechanical designs of space appointment with mobile elements. Relative mechanical motion of nonlinear dynamic system and her the thermal state is described by system of the ordinary differential equations in a matrix kind [1,2]: ) , ( ) ( ) , ( T X B X F T T A X c + = & , (1) ) , , ( ) ( X T T D T X G T c + = & , (2) where Х vector of a mechanical state; vectors of a thermal state of system and an environment; A(T,T c T T , с) a matrix of inertial, dissipative and elastic properties of elements of system; G(X) a matrix of thermal properties; B(X,T), D(T,Tc,X)vectors of controls and disturbances of mechanical and thermal subsystems. Feature of the equations (1),(2) is that mechanical and thermal subsystems are connected through matrixes A,G and entrance disturbances and the controls B,D. It allows to solve problems of the analysis and control of the interconnected mechanical and thermal subsystems. 1. Control of irregular behavior of nonlinear disturbed dynamic system The very important feature of nonlinear disturbed dynamic systems (1), (2) is that in them, at the determined combinations of parameters, occurrence of irregular behavior [3] is possible. We research a possibility and the conditions of a regularization of chaotic motions of a subsystem (1) and of the thermal processes of a subsystem (2) by means of the thermal controlling effect included into a feedback (1). Examples of such systems are nonlinear disturbed by temperature the oscillator (fig.1а) or a mathematical pendulum (fig.1b), which are heat sources of power Q and which make vibratory movements above a motionless body and which we divided on the elementary volumes (elements).
Caring for Frail Older People Living Alone in Italy: Future Housing Solutions and Responsibilities of Family and Public Services, a Qualitative Study

When frail older people age alone in place, with increasing functional limitations, they require support in performing daily living activities. In this respect, it is important to assess their preferences in terms of future housing solutions, and their opinions/orientations on the care responsibilities of both family and public services. The present study aimed to explore these aspects in Italy. Qualitative interviews were carried out in 2019 within the “Inclusive ageing in place” (IN-AGE) research project, involving 120 frail older people who lived at home in three Italian regions (Lombardy, Marche, and Calabria). A content analysis was conducted, and some quantifications of interviewees’ statements were provided. The results revealed that the majority of seniors prefer ageing at home, at least with a personal care assistant (PCA), whereas moving to a nursing home is typically deemed as a last option. Moreover, they considered the family to be primarily responsible for taking care of them, even with the support of public services. In addition, some territorial differences emerged. Strengthening an integrated model of long-term care (LTC) for older people, where both formal and informal supports allow frail older people to age at home, seems thus a good overall policy solution to pursue, with interventions based also on the needs and preferences of both seniors and their respective families.
Implementation of a post-overdose quick response team in the rural Midwest: A team case study

The opioid-involved overdose crisis in the United States has had devastating effects on communities across the country. Post-overdose outreach teams have emerged as one way to reduce overdose risk for individuals who use drugs. Limited literature exists on how these teams are developed and how they operate. Even less is known about these teams in rural locations. This case study explored one rural team’s implementation, including its strengths and barriers to serving participants. Findings from interviews with program staff indicate the team had a consistent procedure for conducting outreach with overdose survivors and family members, had broad support and buy-in from leadership, and were able to clearly articulate the program’s strengths, challenges, and opportunities for growth—including the need for more formal program evaluation. Factors that facilitated implementation included use of a person-centred and non-coercive approach, establishment of team role boundaries, multi-disciplinary collaboration, empathy, and buy-in across agencies and town leadership. Barriers included stigma among citizens, lack of an evaluation plan, difficulty providing outreach to individuals who have unstable housing, and difficulty following up with service agencies. The findings can benefit other jurisdictions, especially small and rural localities seeking to address the drug crisis more effectively.
A Method of Improving Accuracy in Expression Recognition

In order to improve the accuracy of a special kind of facial expression recognition problem, a method for precise face detection and segmentation combined with the particle swarm optimization is proposed. The method uses three key technologies: skin color segmentation, particle swarm search and curve approximation. Firstly, the face contour is roughly obtained through skin color segmentation. Secondly, the accurate face position is detected by particle swarm optimization. Thirdly, the face contour is reduced and regulated further via the curve approximation. The experimental results show that this method can eliminate the interference factor, and then improve the accuracy of expression recognition.
Microplastics do not affect bleaching of Acropora cervicornis at ambient or elevated temperatures

Microplastic pollution can harm organisms and ecosystems such as coral reefs. Corals are important habitat-forming organisms that are sensitive to environmental conditions and have been declining due to stressors associated with climate change. Despite their ecological importance, it is unclear how corals may be affected by microplastics or if there are synergistic effects with rising ocean temperatures. To address this research gap, we experimentally examined the combined effects of environmentally relevant microplastic concentrations (i.e., the global average) and elevated temperatures on bleaching of the threatened Caribbean coral, Acropora cervicornis. In a controlled laboratory setting, we exposed coral fragments to orthogonally crossed treatment levels of low-density polyethylene microplastic beads (0 and 11.8 particles L−1) and water temperatures (ambient at 28 °C and elevated at 32 °C). Zooxanthellae densities were quantified after the 17-day experiment to measure the bleaching response. Regardless of microplastic treatment level, corals in the elevated temperature treatment were visibly bleached and necrotic (i.e., significant negative effect on zooxanthellae density) while those exposed to ambient temperature remained healthy. Thus, our study successfully elicited the expected bleaching response to a high-water temperature. However, we did not observe significant effects of microplastics at either individual (ambient temperature) or combined levels (elevated temperature). Although elevated temperatures remain a larger threat to corals, responses to microplastics are complex and may vary based on focal organisms or on plastic conditions (e.g., concentration, size, shape). Our findings add to a small but growing body of research on the effects of microplastics on corals, but further work is warranted in this emerging field to fully understand how sensitive ecosystems are affected by this pollutant.