Miracle-dz/UniFAR-FTUs huggingface dataset:
Steiner triple systems and cycle structure

Since 1847 when Rev. T.P. Kirkman published his first paper [24], research in Steiner triple systems has grown steadily. With increased and ready access to more powerfiul computers in recent times, this growth has accelerated significantly. Problems are now being solved which were previously considered too 'big' to contemplate using pure Mathematical techniques. Cycle structure is an area of Steiner triple systems which has been largely unexplored and was chosen for this thesis as it offers an opportunity to develop and expand knowledge by applying a mixture of computational and theoretical techniques. For each pair of elements of an STS(v) it is possible to define a cycle list comprising a set of cycles. The length n, of an element of a cycle list is necessarily greater than or equal to 4 and less than or equal to (v-3). The cycle structure of an STS(v) is the collection of all vC 2 cycle lists for that STS(v). An operation that can be carried out on a Steiner triple system is that of cycle switching. Switching an n-cycle in one Steiner triple system will produce a new Steiner triple system that is not usually isomorphic to the original system. The operation of cycle switching is investigated and the survey of 4-cycle switching given by P. Gibbons[12] for the 80 STS(15)s is extended to 6, 8 and 12-cycles. Various well known recursive constructions such as the 'doubling construction' and the 'product construction' produce Steiner triple systems based upon previously given Steiner triple systems. An analysis of these constructions and their effect on the cycle structure of the Steiner triple system produced is considered in this thesis. From this work it is now possible, by knowing the cycle structure of the given system, to predict the cycle structure of the produced Steiner triple system. This is of significant use in producing Steiner triple systems lacking certain forbidden configurations. Perfect and uniform Steiner triple systems may be defined as systems having highly regular cycle structures of two closely related types. Prior to this thesis the total knowledge of perfect and uniform Steiner triple systems was scant and in the case of perfect systems limited to only four values of v. This thesis presents a new technique that produces both perfect and uniforni Steiner triple systems. This technique increases the total number of known perfect Steiner triple systems from four to thirteen and is only limited here by the large size of the systems being produced. A fi.irther area of considerable development in this thesis is the production of previously unknown equivalence classes of Steiner triple systems. This has been achieved by using a combination of cycle switching, an appropriate construction methodology and computer analysis techniques. This thesis is a comprehensive study of the cycle structures of Steiner triple systems and documents some significant new results and techniques that will be of use to anyone interested in Steiner triple systems.
Improved Sensorless FCS-MPCC With Current Pre-Estimation-Based Delay Compensation Integrated for PMSMs Over High-Speed Range

This article proposes a novel current pre-estimation method to solve the delay issues arising from the analog current signal processing circuit (SPC) and the digital execution process, improving the control performance of the sensorless finite control set model predictive current control (FCS-MPCC) strategies used in permanent magnet synchronous motor (PMSM) drives. First, the PMSM model used for sensorless FCS-MPCC is established. Then, the mechanisms of the two kinds of delays are detailed and their negative impacts on the FCS-MPCC control performance are explained, especially in the high-speed range. Third, the proposed compensation technique based on three sequential procedures including delay calculation, phase calculation, and current pre-estimation is presented. By using the pre-estimated currents, the sensorless FCS-MPCC strategy with these delays compensated is achieved. Finally, the experiment is conducted on three-phase PMSMs to verify the effectiveness of the proposed compensation and control strategies.
Spanningspiders and lig ht-splittingswitches

Motivated by a problem in the design of optical networks, we ask when a graph has a spanning spider (subdivision of a star), or, more generally, a spanning tree with a bounded number of branch vertices. We investigate the existence of these spanning subgraphs in analogy to classical studies of Hamiltonicity. c
Few-Shot Learning-Based Light-Weight WDCNN Model for Bearing Fault Diagnosis in Siamese Network

In this study, bearing fault diagnosis is performed with a small amount of data through few-shot learning. Recently, a fault diagnosis method based on deep learning has achieved promising results. Most studies required numerous training samples for fault diagnosis. However, at manufacturing sites, it is impossible to have enough training samples to represent all fault types under all operating conditions. In addition, most studies consider only accuracy, and models are complex and computationally expensive. Research that only considers accuracy is inefficient since manufacturing sites change rapidly. Therefore, in this study, we propose a few-shot learning model that can effectively learn with small data. In addition, a Depthwise Separable Convolution layer that can effectively reduce parameters is used together. In order to find an efficient model, the optimal hyperparameters were found by adjusting the number of blocks and hyperparameters, and by using a Depthwise Separable Convolution layer for the optimal hyperparameters, it showed higher accuracy and fewer parameters than the existing model.
Fuzzy Kernel Alignment With Application to Attribute Reduction of Heterogeneous Data

Fuzzy similarity relation is a function to measure the similarity between two samples. It is widely used to learn knowledge under the framework of fuzzy machine learning. The selection of a suitable fuzzy similarity relation is important for the learning task. It has been pointed out that fuzzy similarity relations can be brought into the framework of kernel functions in machine learning. This fact motivates us to study fuzzy similarity relation selection for fuzzy machine learning utilizing kernel selection methods in machine learning. Kernel alignment is a kernel selection method that is effective and has low computational complexity. In this paper, we present novel methods for fuzzy similarity relation selection based on the kernel alignment, and their use in attribution reduction for heterogeneous data. First, we define an ideal kernel for classification problems, based on which a novel fuzzy kernel alignment model is proposed. Second, we present a method for the fuzzy similarity relation selection based on the minimization of the fuzzy alignment between the defined ideal kernel and a kernel for the learning problem at hand. In order to show the correctness of this selection method, we prove that the lower bound of the classification accuracy of a support vector machine will increase with the decrease of the fuzzy alignment value. Furthermore, we apply the proposed fuzzy similarity relation selection to attribute reduction for heterogeneous data. Finally, we present experimental results to show that the proposed method of fuzzy similarity relation selection based on the fuzzy kernel alignment is effective.
Some Activity Predicates as Accomplishments

Juwon Lee. 2016. Some Activity Predicates as Accomplishments. Language and Information 20.2, 117-143. In this paper I argue that some "activity" predicates in Korean are actually a kind of accomplishment rather than activity, unlike English counterparts. As evidence for this recategorization, failed attempt interpretation, ambiguity with in-adverbial or keuy 'almost', and non-ambiguity with tasi 'again' are discussed. This type of accomplishment is called activity-accomplishment here and this accomplishment analysis is extended to other kinds of "activity" verbs in Korean, manner of speaking verbs and perception verbs. I also show that in addition to lexical activity-accomplishment, some derived activity-accomplishments involving resultative or causative constructions support the existence of activity-accomplishment in Korean. (Kyung Hee University)
Parametric Empirical Bayes Test and Its Application to Selection of Wavelet Threshold

In this article, we propose a new method for selecting level dependent threshold in wavelet shrinkage using the empirical Bayes framework. We employ both Bayesian and frequentist testing hypothesis instead of point estimation method. The best test yields the best prior and hence the more appropriate wavelet thresholds. The standard model functions are used to illustrate the performance of the proposed method and make comparisons with other traditional methods.
Academic Performance Prediction of At-Risk Students using Machine Learning Techniques

Imparting quality education is a top priority of higher education institutions. Leaving at risk students unattended would adversely impact the quality of education. Predicting the academic performance of students is one of the basis for improving the quality of education, as it would help the institution to take early and timely measures to support the low-performing students and improve their performance. At the same time, it has identified that the prediction of student performance considered as challenging one due to large dataset in educational environment. However, Educational Data Mining (EDM) using machine learning techniques is an emerging research area, which allows the researchers to effectively process and evaluate the educational data collected from different sources. In this paper, we propose the use of support vector machine (SVM) on an imbalanced dataset to predict the academic performance of students.
Wideband non-traveling-wave triple-mode slotline antenna

Design approach of a novel, triple-mode wideband slotline antenna is proposed and studied. The proposed antenna is realised and implemented by employing the multiple resonant modes within a narrow slotline radiator, rather than utilising the traveling-wave effect. At first, a triple-digit, fork-like microstrip tuning stub is used to excite the first and the second odd-order mode within a slim, 3/2-wavelength slotline radiator. Then, a pair of slotline stubs is introduced near the E-field nulls of the third odd-order mode. By finely tuning the parameters of the microstrip/slotline stubs, the three radiation modes are perturbed and merged to generate a wideband, radiation characteristic with three resonances. Prototype antennas are then fabricated and measured. Finally, the design approach is experimentally validated. It is shown that the proposed antenna's radiation bandwidth has been effectively increased to 33.2% while keeping a single, basic-form narrow slotline radiator with a simple, non-traveling-wave configuration.
Better together: novel methods for measuring and modeling development of executive function diversity while accounting for unity

Executive functions (EFs) are linked to positive outcomes across the lifespan. Yet, methodological challenges have prevented precise understanding of the developmental trajectory of their organization.We introduce novel methods to address challenges for both measuring and modeling EFs using an accelerated longitudinal design with a large, diverse sample of students in middle childhood (N = 1,286; ages 8 to 14). We used eight adaptive assessments hypothesized to measure three EFs, working memory, context monitoring, and interference resolution. We deployed adaptive assessments to equate EF challenge across ages and a data-driven, network analytic approach to reveal the evolving diversity of EFs while simultaneously accounting for their unity.Using this methodological paradigm shift brought new precision and clarity to the development of these EFs, showing these eight tasks are organized into three stable components by age 10, but refinement of composition of these components continues through at least age 14.
Some Properties of Solution to Semidefinite Complementarity Problem

In this paper, we discuss the nonemptyness and boundedness of the solution set for P*-semidefinite complementarity problem by using the concept of exceptional family of elements for complementarity problems over the cone of semidefinite matrices, and obtain a main result that if the corresponding problem has a strict feasible point, then its solution set is nonemptyness and boundedness.
Effect of Bovine MEF2A Gene Expression on Proliferation and Apoptosis of Myoblast Cells

Myocyte enhancer factor 2A (MEF2A) is a member of the myocyte enhancer factor 2 family. MEF2A is widely distributed in various tissues and organs and participates in various physiological processes. This study aimed to investigate the effect of MEF2A expression on the proliferation and apoptosis of bovine myoblasts. CCK8, ELISA, cell cycle, and apoptosis analyses were conducted to assess cell status. In addition, the mRNA expression levels of genes associated with bovine myoblast proliferation and apoptosis were evaluated using RT-qPCR. The results showed that the upregulation of MEF2A mRNA promoted the proliferation rate of myoblasts, shortened the cycle process, and increased the anti-apoptotic rate. Furthermore, the RT-qPCR results showed that the upregulation of MEF2A mRNA significantly increased the cell proliferation factors MyoD1 and IGF1, cell cycle factors CDK2 and CCNA2, and the apoptotic factors Bcl2 and BAD (p < 0.01). These results show that the MEF2A gene can positively regulate myoblast proliferation and anti-apoptosis, providing a basis for the analysis of the regulatory mechanism of the MEF2A gene on bovine growth and development.
A revised test of cosmic curvature at high redshifts: the distance sum rule

Ultra-compact structure in radio quasars, with milliarcsecond angular sizes measured by very-long-baseline interferometry (VLBI), provides an important source of angular diameter distances that can be observed up to higher redshifts. In this paper, with the latest catalog of galactic-scale strong gravitational lensing systems and the VLBI observation of milliarcsecond compact structure in intermediate-luminosity quasars, we place constraints on the curvature of the universe through the well-known distance sum rule, without assuming any fiducial cosmological model. Assuming power-law density profiles for the total mass density of lensing galaxies ($\rho\sim r^{-\gamma}$), we find that, although the zero cosmic curvature is still included within $2 \sigma$ confidence level, a closed universe is seemed to be more favored in our analysis. In addition, in the framework of a more general lens model which allows the luminosity density profile $\rho\sim r^{-\alpha}$ to be different from that of the total-mass density profile $\nu\sim r^{-\delta}$, a weaker constraint on the curvature ($\Omega_k<0.197$ at 68\% confidence level)is obtained indicates that a more general lens model does have a significant impact on the measurement of cosmic curvature. Finally, based on the mock samples of strong gravitational lenses and quasars with the current measurement accuracy, we find that with about 16000 strong lensing events (observed by the forthcoming LSST survey) combined with the distance information provided by 500 compact uv-coverage, one can constrain the cosmic curvature with an accuracy of $\Delta \Omega_k\simeq 10^{-3}$, which is comparable to the precision of Planck 2015 results.
The Sobolev space of half-differentiable functions and quasisymmetric homeomorphisms

Abstract In this paper, we give an interpretation of some classical objects of function theory in terms of Banach algebras of linear operators in a Hilbert space. We are especially interested in quasisymmetric homeomorphisms of the circle. They are boundary values of quasiconformal homeomorphisms of the disk and form a group QS ⁡ ( S 1 ) ${\operatorname{QS}(S^{1})}$ with respect to composition. This group acts on the Sobolev space H 0 1 / 2 ⁢ ( S 1 , ℝ ) ${H^{1/2}_{0}(S^{1},\mathbb{R})}$ of half-differentiable functions on the circle by reparameterization. We give an interpretation of the group QS ⁡ ( S 1 ) ${\operatorname{QS}(S^{1})}$ and the space H 0 1 / 2 ⁢ ( S 1 , ℝ ) ${H^{1/2}_{0}(S^{1},\mathbb{R})}$ in terms of noncommutative geometry.
NEUTRON REPULSION - POWERS BEYOND THE DREAMS OF SCIENTIFIC FICTION

The purpose of this review is to share experimental evidence of neutron repulsion with others - and to show graphically why elusive neutron repulsion was overlooked as the likely source of “powers beyond the dreams of scientific fiction” in the development of nuclear energy - before neutron repulsion is presented for public discussion at the London GeoEthics Conference on Climate Changeon September 8-9, 2016. Aston first suggested atomic “powers beyond the dreams of scientific fiction” in the last paragraph of his 1922 Nobel Lecture, ten year before the neutron was discovered in 1932. Aston’s expression of nuclear “packing fraction” was largely replaced in nuclear science textbooks after 1935 by thecunningconcept of nuclear “binding energy,” based on the neutron-proton model of the atomic nucleus. When Aston repeated his Nobel Lecture at the Imperial University of Tokyo in 1936, a talented 19-year-old student apparently recognized the discrepancy between measured “packing fraction” and calculated “binding energy. ”Soon after neutron-induced fission of uranium was first reported in early 1939, other scientists independently reported numbers of secondary neutronsreleased during fission that might induce aself-sustaining chain of nuclear reactions. This became the basis for nuclear secrets and atomic bomb production during WWII. Three-dimensional plots of precise atomic rest mass data from Brookhaven National Laboratory revealed neutron repulsion as apowerful, short-range nuclear force in 2000. Neutron repulsion was later identified as the trigger for neutron-emission from pulsar cores of ordinary stars, like the Sun, and the primary source of solar energy.
Water Classification Using Convolutional Neural Network

The classification of water sources is a challenging task due to the low contrast texture features, the visual similarities between them, and the causes posed by image acquisition with different camera angles and placements. The various image enhancement techniques, i.e., Unsharp Masking (UM), Histogram Equalization (HE), Contrast Limited Adaptive Histogram Equalization (CLAHE), and Contrast Stretching, were used to highlight the contrast and texture features of water images. The enhanced image samples were then fed to the proposed Convolutional Neural Network (CNN)-based model named WaterNet (WNet) for classification. From all employed image enhancement techniques, Contrast Limited Adaptive Histogram Equalization (CLAHE) provides better results in terms of contrast and texture features of water. CLAHE also improved the classification performance of the proposed model, with an accuracy of 97%. For comparison, experiments have also been performed on state-of-the-art pre-trained models, which are DenseNet-201, Inception_ResNet_v2, Inception_v3, and Mobile-Net. Comparison shows that the proposed technique achieves better accuracy in comparison with the state-of-the-art methods.
Low-Cost Wireless Monitoring and Control: A Case Study for Industrial Implementation

In this study, a low-cost wireless industrial system is designed and implemented in a local pharmaceutical factory for monitoring and control. ESP8266 modules were utilized to establish wireless communication among various input and output devices in the factory. The master-slave (i.e., server-client) technology using ESP8266 modules was adopted for the communication topology where all clients can be connected to various types of sensors (e.g., to measure variables such as temperature, humidity, and pressure) and outputs (e.g., relays, lights, and output devices) for control purposes. It is in fact a simplified SCADA system implemented using low-cost WiFi microchips for monitoring and control. In addition, an HTML webpage was designed as a GUI for monitoring the sensors' measurements and manually controlling some output devices that are distributed normally in factories. Moreover, a data logger was also designed and implemented using Google Sheets for mainly saving the data (i.e., measurement of real-time parameter variations) and for generating informative reports for users and management.
Correlations between Ratings and Technical Measurements in Hand-Intensive Work

An accurate rating of hand activity and force is essential in risk assessment and for the effective prevention of work-related musculoskeletal disorders. However, it is unclear whether the subjective ratings of workers and observers correlate to corresponding objective technical measures of exposure. Fifty-nine workers were video recorded while performing a hand-intensive work task at their workplace. Self-ratings of hand activity level (HAL) and force (Borg CR10) using the Hand Activity Threshold Limit Value® were assessed. Four ergonomist observers, in two pairs, also rated the hand activity and force level for each worker from video recordings. Wrist angular velocity was measured using inertial movement units. Muscle activity in the forearm muscles flexor carpi radialis (FCR) and extensor carpi radialis (ECR) was measured with electromyography root mean square values (RMS) and normalized to maximal voluntary electrical activation (MVE). Kendall’s tau-b correlations were statistically significant between self-rated hand activity and wrist angular velocity at the 10th, 50th, and 90th percentiles (0.26, 0.31, and 0.23) and for the ratings of observers (0.32, 0.41, and 0.34). Significant correlations for force measures were found only for observer-ratings in five of eight measures (FCR 50th percentile 0.29, time > 10%MVE 0.43, time > 30%MVE 0.44, time < 5% −0.47) and ECR (time > 30%MVE 0.26). The higher magnitude of correlation for observer-ratings suggests that they may be preferred to the self-ratings of workers. When possible, objective technical measures of wrist angular velocity and muscle activity should be preferred to subjective ratings when assessing risks of work-related musculoskeletal disorders.
Progressive fibrotic interstitial lung disease

ABSTRACT Many interstitial lung diseases (ILDs) share mechanisms that result in a progressive fibrosing phenotype. In Brazil, the most common progressive fibrosing interstitial lung diseases (PF-ILDs) are chronic hypersensitivity pneumonitis, idiopathic pulmonary fibrosis, unclassified ILD, and connective tissue diseases. PF-ILD is seen in approximately 30% of patients with ILD. Because PF-ILD is characterized by disease progression after initiation of appropriate treatment, a diagnosis of the disease resulting in fibrosis is critical. Different criteria have been proposed to define progressive disease, including worsening respiratory symptoms, lung function decline, and radiological evidence of disease progression. Although the time elapsed between diagnosis and progression varies, progression can occur at any time after diagnosis. Several factors indicate an increased risk of progression and death. In the last few years, antifibrotic drugs used in patients with idiopathic pulmonary fibrosis have been tested in patients with PF-ILD. The effects of nintedanib and placebo have been compared in patients with PF-ILD, a mean difference of 107.0 mL/year being observed, favoring nintedanib. The U.S. Food and Drug Administration and the Brazilian Health Regulatory Agency have approved the use of nintedanib in such patients on the basis of this finding. Pirfenidone has been evaluated in patients with unclassified ILD and in patients with other ILDs, the results being similar to those for nintedanib. More studies are needed in order to identify markers of increased risk of progression in patients with ILD and determine the likelihood of response to treatment with standard or new drugs.