Miracle-dz/UniFAR-FTUs huggingface dataset:
Remaining Useful Life Estimation of Aero-Engines with Self-Joint Prediction of Continuous and Discrete States

The remaining useful life (RUL) estimation generally suffer from this problem of lacking prior knowledge to predefine the exact failure thresholds for machinery operating in dynamic environments. In this case, dynamic thresholds depicted by discrete states are effective to estimate the RUL of dynamic machinery. Currently, only few work considers the dynamic thresholds, and adopt different algorithms to predict the continuous and discrete states separately, which largely increases the complexity of the learning process. In this paper, we propose a novel prognostics approach for RUL estimation of aero-engines with self-joint prediction of continuous and discrete states within one learning framework. With modeling capability of self-adapting structure and parameters online, the quantized kernel recursive least squares (QKRLS) algorithm is introduced to predict the degrading states and also determine the discrete states with the kernel centers. The self-evolving dynamic kernel centers obtained during building predictors are automatically assigned as the discrete states for different engines without predefining them. Then, the RUL is estimated conveniently once the predicted degrading signals fall into the final fault state based on a distance metric. Finally, the results from turbofan engine datasets demonstrate the superiority of the proposed approach compared to other popular approaches.
Scalable Gaussian process inference using variational methods

Gaussian processes can be used as priors on functions. The need for a flexible, principled, probabilistic model of functional relations is common in practice. Consequently, such an approach is demonstrably useful in a large variety of applications. Two challenges of Gaussian process modelling are often encountered. These are dealing with the adverse scaling with the number of data points and the lack of closed form posteriors when the likelihood is non-Gaussian. In this thesis, we study variational inference as a framework for meeting these challenges. An introductory chapter motivates the use of stochastic processes as priors, with a particular focus on Gaussian process modelling. A section on variational inference reviews the general definition of Kullback-Leibler divergence. The concept of prior conditional matching that is used throughout the thesis is contrasted to classical approaches to obtaining tractable variational approximating families. Various theoretical issues arising from the application of variational inference to the infinite dimensional Gaussian process setting are settled decisively. From this theory we are able to give a new argument for existing approaches to variational regression that settles debate about their applicability. This view on these methods justifies the principled extensions found in the rest of the work. The case of scalable Gaussian process classification is studied, both for its own merits and as a case study for non-Gaussian likelihoods in general. Using the resulting algorithms we find credible results on datasets of a scale and complexity that was not possible before our work. An extension to include Bayesian priors on model hyperparameters is studied alongside a new inference method that combines the benefits of variational sparsity and MCMC methods. The utility of such an approach is shown on a variety of example modelling tasks. We describe GPflow, a new Gaussian process software library that uses TensorFlow. Implementations of the variational algorithms discussed in the rest of the thesis are included as part of the software. We discuss the benefits of GPflow when compared to other similar software. Increased computational speed is demonstrated in relevant, timed, experimental comparisons.
Improved local quantile regression

We investigate a new kernel-weighted likelihood smoothing quantile regression method. The likelihood is based on a normal scale-mixture representation of asymmetric Laplace distribution (ALD). This approach enjoys the same good design adaptation as the local quantile regression (Spokoiny et al., 2013, Journal of Statistical Planning and Inference, 143, 1109–1129), particularly for smoothing extreme quantile curves, and ensures non-crossing quantile curves for any given sample. The performance of the proposed method is evaluated via extensive Monte Carlo simulation studies and one real data analysis.
Review of Chemical, Biological, and Epistemological Elements: Mamaq Tradition

Mamaq by the ancestors of the Sasak people was an activity of chewing betel nut, lime, betel leaf, and tobacco, and ending with shrinkage. Betel leaves contain glycosides, steroids, triterpenoids, flavonoids, tannins, and anthraquinones. These compounds contain antimicrobial activity that can fight Staphylococcus aureus, Escherichia coli, and Candida albicans fungi. Meanwhile, whiting is a strong base because it has a pH of 11-12.5. This is because in the mouth there is saliva which can maintain a pH of around 6.8. Saliva contains phosphate buffer solutions H2PO4- and HPO42-. And gambir contains a component in the form of catechins which function as antioxidants and antibacterials. The purpose of this research is to study philosophical values, especially epistemology, which investigates the origin, and composition of methods and knowledge related to mamaq philosophy and natural science concepts, especially chemistry, and compounds, and what reactions occur in the mamaq process that has not been revealed. The study uses the library method. From the results of thestudy, it was concluded that in addition to the philosophy in the ingredients for mamaq it can also be described the chemical compounds contained in the ingredients for mamaq, starting from whiting, green betel leaf, gambier, and areca nut.
Adaptive Threshold And Piecewise Fitting For Iris Localisation

Machine vision needs detectors to get features and properties of objects in each image to be used for ensuring the effectiveness of each study conducted. The most recognisable Canny edge detection method aims to lessen noise and eliminate unwanted edge by employing threshold values and hysteresis for localisation advantages. Canny method uses a high threshold and a low threshold to decrease of false positive pixel edges and to describe the contours in the image crucially as compared to use one fixed threshold value for the maximum gradient is not the best option. Nevertheless, using two unchanged threshold values still do not guarantee to provide the best results because the image contains huge variations. Previously, adaptive thresholds have been introduced for specific domain only. Here, a technique to determine the threshold values from the foreground and background image pixels in the global and local image will be used for further analysis. This approach involves partitioning an image into several similar size blocks at multiple resolution levels. Then, a sampling procedure uses on global and local images to acquire the best threshold value by selecting the highest between the class variance values. Finally, piecewise cubic spline will completely segment the boundary for iris and pupil region. Experiments have been done on CASIA V2 datasets. The results show that edge image obtained outperform the Canny method and previous work. Iris localization image obtained also more accurate compared to Hough method.
The effects of on-line math games and e-books use on elementary student achievement

Game-based learning and the use of e-books is becoming increasingly more supported in classrooms as methods of increasing both student engagement and student achievement in all curricular areas. The purpose of this literature review is to examine current research on the effects of online math games and e-books on elementary student engagement and academic achievement. Over thirty peer-reviewed journal articles published in the last ten years are critically reviewed and analyzed. The findings show that online game-based learning and e-books can be effective tools within the confines of the elementary classroom, as long as careful consideration is given to student learning attitudes, how the e-books and online games are integrated into the curriculum, and the fidelity in which these programs are being used. Recommendations for educators are given for future inclusion of online game-based learning and digital texts in their own classrooms.
Analisis Penerapan Sistem Perawatan dengan Menggunakan Metode Reliability Centered Maintenance (RCM) pada Cement Mill Type Tube Mill di PT Cemindo Gemilang Medan

PT Cemindo Gemilang Medan merupakan salah satu perusahaan yang bergerak dibidang industri manufaktur yang menghasilkan produk berupa semen dengan kapasitas produksi 30 ton/jam. Salah satu proses yang berlangsung adalah proses penggilingan material pembuatan semen yang berlangsung di Cement Mill. Berdasarkan data-data yang didapat dari departemen produksi, diambil data selama 6 bulan pada periode bulan Januari 2022 – Juni 2022. Diketahui bahwa mesin Cement Mill mengalami total downtime yang mengakibatkan proses produksi menurun, dimana proses produksi berlangsung secara kontinyu yaitu 24 jam per hari. Untuk mengatasi permasalahan tersebut maka dilakukan analisa penerapan sistem perawatan dengan menggunakan metode Reliability Centered Maintenance (RCM) melalui pendekatan Failure Mode and Effect Analysis (FMEA) sebuah prosedur struktural guna mengetahui dan mencegah terjadinya kegagalan dengan menentukan faktor kualitatif komponen kritis dan menghitung nilai resiko prioritas (RPN). Menurut Anthony M.Smith, 1992 (Shinta, dkk 2021) penelitian dengan metode RCM (Reliablity Centered Maintenance), secara umum dibagi menjadi 2 yaitu, secara kualitatif dan secara kuantitatif. Analisa kualitatif terdiri dari FMEA (Failure Mode and Effect Analysis), dan LTA (Logic Tree Analysis). Sedangkan analisa kuantitatif terdiri dari perhitungan MTBF (Mean Time Between Failure), MTTR (Mean Time to Repair), penentuan reliability, dan failure rate. Dari hasil analisa kualitatif terdapat 4 komponen MSI (Maintenance Significant Item), yaitu mill bearing, mill diafraghm, mill fan dan vibrating sensor. Dari hasil Analisa kuantitatif didapatkan subsistem dengan reliability rate berdasarkan Inherent Availability-nya yang paling rendah yaitu mill fan sebesar 79,92%. Tindakan dan rencana perawatan yang disarankan berdasarkan metode RCM (Reliablity Centered Maintenance) yaitu melakukan pengecekan secara rutin, membuat re-design untuk mengurangi failure, serta melakukan training pada bagian maintenance mengenai konsep perawatan.
ORB Feature based Matching of Two-Dimensional Electrophoresis Gel Images

Abstract. An alternative approach was applied for matching two-dimensional Protein gel Electrophoresis images for real-time applications use. For the feature extraction of protein spot the ORB feature descriptor was used. The matching of extracted ORB features was achieved using the Brute Force matcher. Lastly, the planar homography transformation matrix is found and perspective transform applied gaining the warped two-dimensional electrophoresis image. The matching performed in 2.1 second of selected gel region having 2855x1176 initial resolution gel image with ~97% accuracy using standard desktop computing.
Nexus of Gender and Disability: An Intersectional Study on Shaping Lives of University Students

The current study attempted to explore the intersection of gender and disability in university students. It was observed that how the nexus of gender and disability shapes lives. Disability poses many problems for each individual. However, in the context of Pakistani society, the intersection of disability with gender is not explored much. The purpose of this research was to understand the differences between girls and boys as they face disability. This was a qualitative study. The students of public and private sector universities of Lahore were interviewed in this phenomenological study. A total number of eight (8) students including 4 male and 4 female students with physical and visual disability were interviewed. The gender differences were examined through qualitative thematic content analysis. The findings showed that disability tends to effect the social inclusion of the people with special needs. The nexus of disability and gender marginalize women more as compared to men. Women lose confidence which, in turn, impacts their emotional and psychological well-being. The current study is one of the very few researches which explored the intersection of gender and disability among the university students of Lahore, Pakistan. On the basis of the findings, future research could be conducted on a bigger population and with different research designs. Additionally, this study is a step in the direction of raising awareness regarding the added issues faced by girls and women with disabilities.
Phylogenetic relationships of the West African mud turtle (Pelusios castaneus) on the islands of São Tomé and Príncipe, West Central Africa

On the island nation of São Tomé and Príncipe, West Africa, only one species of terrapin has been recorded: the West African mud turtle, Pelusios castaneus. Here, we use a mtDNA phylogenetic approach to shed light on the geographical origin of Pelusios castaneus on both islands. Our results indicate several independent colonisations from different African mainland regions (Nigeria, Ivory Coast, Sierra Leone and Congo). However, it is still unclear if the species arrived on the islands by natural dispersal (e.g., through vegetation rafts) or by human agency (e.g., as a food source). Our work provides important insights into the origins of P. castaneus in São Tomé and Príncipe, but a more in-depth study is needed to fully understand the origins and evolutionary histories of these populations.
Understanding the gyroscope sensor: a quick guide to teaching rotation movements using a smartphone

Currently, the number of smartphones with an embedded gyroscope sensor has been increasing due games whose performance relies on 3D augmented reality. In general, teaching papers on the gyroscope sensor address very simple spatial configuration, where the fixed rotation axis coincides to the z-axis of the smartphone. This work presents five experimental setups with different spatial orientations of a smartphone on a turntable. The total angular velocity vector of the turntable is constant, but its projections on the three fixed Cartesian axes of the smartphone varies for the five spatial orientations investigated. For the sake of consistency, the magnitude of the vector sum of the three angular velocities components yielded by the gyroscope sensor was checked by video analysis using the free software, Tracker. The internal consistency between the results provided by this video analysis technique and data from the gyroscope assures us this sensor is reliable for teaching proposals. The main goals of this paper are (i) encourage teachers to effectively incorporate the gyroscope sensor of smartphones in to their classrooms, especially in high schools and undergraduate physics and engineering courses; (ii) spread in the academic syllabus the Tait–Bryan convention, a very intuitive way to perform 3D rotations and; (iii) explain how to interpret data of the three components of angular velocity obtained by the gyroscope sensor in different spatial orientations.
Comparing Front-to-Front and Front-to-End Heuristics in Bidirectional Search

Most recent theoretical and algorithmic work in bidirectional heuristic search (BiHS) used front-to-end (F2E) heuristics that estimate the distance to the start and goal states. In this paper, we start exploring front-to-front (F2F) heuristics, which estimate the distance between any pair of states. Devising efficient algorithms that use F2F heuristics is a challenging task. Thus, it is important to first understand the benefits of using F2F heuristics compared to F2E heuristics. To this end, we theoretically and experimentally demonstrate that there is a great potential in using F2F heuristics implying that F2F BiHS is a promising area of future research.
Effect of Heat Treatments and Carbon Content on the Damping Properties of Structural Steel

Low- and medium-carbon structural steel components face random vibration and dynamic loads (like earthquakes) in many applications. Thus a modification to improve their mechanical properties, essentially damping properties, is required. The present study focuses on improving and developing these properties, significantly dampening properties, without losing the other mechanical properties. The specimens used in the present study are structural steel ribbed bar ISO 6935 subjected to heating temperatures of (850, 950, and 1050) ˚C, and cooling schemes of annealing, normalizing, sand, and quenching was selected. The damping properties of the specimens were measured experimentally with the area under the curve for the loading and unloading paths experienced from the tensile test. Considering the effect of different parameters on the damping properties, such as heat treatment temperatures, cooling rates, and carbon content, the results show that the damping properties in the annealing process at different temperatures have interesting damping properties, among other processes. Also, the highest damping energy for the annealing cooling scheme was attained at a heating temperature of 1050 ˚C, irrespective of the carbon content. Finally, better damping properties for the medium carbon content of (0.299%C) is achieved for all types of heat treatment process compared with a low carbon content of (0.188% C); and, in general, with increasing carbon content from medium to low, steel response to heat treatment increases and better damping properties are obtained.
Systematic Analysis of Smooth Muscle and Cartilage Ring Formation during Mouse Tracheal Tubulogenesis

The trachea tube is the exclusive route to allow gas exchange between the external environment and the lungs. Recent studies have shown the critical role of mesenchymal cells in tracheal tubulogenesis. Improved methods for studying the dynamics of the tracheal mesenchyme development are needed to investigate the cellular and molecular mechanisms during tracheal tubulogenesis. Here, we describe a detailed protocol for a systematic analysis of tracheal tube development to enable observing tracheal smooth muscle (SM) and cartilage ring formation. We describe immunostaining, confocal and stereomicroscopy imaging, and quantitative methods to study the process of tracheal SM and cartilage ring development, including SM cell alignment, polarization, and changes in cell shape as well as mesenchymal condensation. The technologies and approaches described here not only improve analysis of the patterning of the developing trachea but also help uncover the mechanisms underlying airway disease. This protocol also provides a useful technique to analyze cell organization, polarity, and nuclear shape in other organ systems.
Growth Increase in the Herbaceous Plant Centella asiatica by the Plant Growth-Promoting Rhizobacteria Priestia megaterium HyangYak-01

Centella asiatica is a traditional herbaceous plant with numerous beneficial effects, widely known for its medicinal and cosmetic applications. Maximizing its growth can lead to beneficial effects, by focusing on the use of its active compounds. The use of plant growth-promoting rhizobacteria (PGPR) is known to be an alternative to chemical fertilizers. In this study, we used the PGPR Priestia megaterium HY-01 to increase the yield of C. asiatica. In vitro assays showed that HY-01 exhibited plant growth-promoting activities (IAA production, denitrification, phosphate solubilization, and urease activity). Genomic analyses also showed that the strain has plant growth-promoting-related genes that corroborate with the different PGP activities found in the assays. This strain was subsequently used in field experiments to test its effectiveness on the growth of C. asiatica. After four months of application, leaf and root samples were collected to measure the plant growth rate. Moreover, we checked the rhizosphere microbiome between the treated and non-treated plots. Our results suggest that treatment with Hyang-yak-01 not only improved the growth of C. asiatica (leaf length, leaf weight, leaf width, root length, root width, and chlorophyll content) but also influenced the rhizosphere microbiome. Biodiversity was higher in the treated group, and the bacterial composition was also different from the control group.
Hydrogel-Based Biosensors for Effective Therapeutics

Nanotechnology and polymer engineering are navigating toward new developments to control and overcome complex problems. In the last few decades, polymer engineering has received researchers’ attention and similarly, polymeric network-engineered structures have been vastly studied. Prior to therapeutic application, early and rapid detection analyses are critical. Therefore, developing hydrogel-based sensors to manage the acute expression of diseases and malignancies to devise therapeutic approaches demands advanced nanoengineering. However, nano-therapeutics have emerged as an alternative approach to tackling strenuous diseases. Similarly, sensing applications for multiple kinds of analytes in water-based environments and other media are gaining wide interest. It has also been observed that these functional roles can be used as alternative approaches to the detection of a wide range of biomolecules and pathogenic proteins. Moreover, hydrogels have emerged as a three-dimensional (3D) polymeric network that consists of hydrophilic natural or synthetic polymers with multidimensional dynamics. The resemblance of hydrogels to tissue structure makes them more unique to study inquisitively. Preceding studies have shown a vast spectrum of synthetic and natural polymer applications in the field of biotechnology and molecular diagnostics. This review explores recent studies on synthetic and natural polymers engineered hydrogel-based biosensors and their applications in multipurpose diagnostics and therapeutics. We review the latest studies on hydrogel-engineered biosensors, exclusively DNA-based and DNA hydrogel-fabricated biosensors.
A separable strong-anisotropy approximation for pure qP-wave propagation in transversely isotropic media

ABSTRACTThe wave equation can be tailored to describe wave propagation in vertical-symmetry axis transversely isotropic (VTI) media. The qP- and qS-wave eikonal equations derived from the VTI wave equation indicate that in the pseudoacoustic approximation, their dispersion relations degenerate into a single one. Therefore, when using this dispersion relation for wave simulation, for instance, by means of finite-difference approximations, both events are generated. To avoid the occurrence of the pseudo-S-wave, the qP-wave dispersion relation alone needs to be approximated. This can be done with or without the pseudoacoustic approximation. A Pade expansion of the exact qP-wave dispersion relation leads to a very good approximation. Our implementation of a separable version of this equation in the mixed space-wavenumber domain permits it to be compared with a low-rank solution of the exact qP-wave dispersion relation. Our numerical experiments showed that this approximation can provide highly accurate wavefi.
Ergodicity and extinction in a stochastic susceptible-infected-recovered-susceptible epidemic model with influence of information

ABSTRACT An epidemic model with stochastic contact transmission coefficient takes into account white noise and the influence of information. Sufficient conditions for the extinction and persistence of the disease are expressed. The existence of a stationary distribution and the ergodic property are proved. The peak of infected population can be decreased by information. The analytical results are showed by simulations and the influence of white noise and information on the dynamics of epidemics are evaluated.