Miracle-dz/UniFAR-FTUs huggingface dataset:
Piecewise Feature Extraction and Artificial Neural Networks: an Approach towards Curve Reconstruction

Background/Objectives: Reconstruction of shapes from unorganized data points is a problem with lot of practical significance in which a piecewise linear approximation to the shape is computed from the sample of the unknown shape. Methods/Statistical Analysis: An approach based on reconstruction of curves by using the feature points as control points is presented. At the transmission end the curve is represented using the feature points and at the receiver side the reconstruction of curve is established by optimizing the parameters of a radial basis function (RBF) neural network. Findings: The method reduces the complexity in terms of time and space. In other words it reduces the informational complexity of the RBF network for the problem of curve reconstruction. It also allows for noise in the data by using the inherent capabilities of a RBF neural network. Applications/Improvements: Scenes generated by modeling and animation using multimedia techniques contain curves and surfaces and thus the presented approach is useful in efficient transmission of images and video sequences.
Impact of the COVID-19 Pandemic on Community Consumption of Antibiotics for Systemic Use and Resistance of Invasive Streptococcus pneumoniae in Slovenia

The present study aims to investigate the impact of the COVID-19 pandemic on community antibiotic consumption and the resistance of invasive Streptococcus pneumoniae (2015–2022) to penicillin in Slovenia. During the pandemic in 2020 and 2021, the total use of antibiotics for systemic use decreased by 23.5% and 24.3%, expressed in defined daily doses per 1000 inhabitants per day (DID), while the use of penicillins, macrolides and broad-spectrum penicillins decreased by 30%, 20% and by 17.5%, respectively, and that of broad-spectrum macrolides fell by 17.1%. The incidence of invasive pneumococcal diseases (IPD) in Slovenia had a large decline during the pandemic. Decreased resistance to macrolides was significantly associated with decreased use of macrolides, while for penicillins the correlation could not be statistically confirmed. The proportion of PCV13 serotypes in IPD in Slovenia decreased after the introduction of the vaccine in the national programme, falling from 81.6% in 2015 to 45.5% in 2022. We noticed a decrease in the serotypes 1, 14, 9V, 7F, 4, 6A and an increase in the serotypes 3, 8, 22F, 11A, 23A and 15A. National interventions during the COVID-19 pandemic substantially decreased outpatients’ antibiotic consumption, as well as incidence and resistance of invasive S. pneumoniae.
Morphological Description and Weight-Length Relationship of the Intertidal Sipuncula Siphonosoma australe (Keferstein, 1865) along the Central Coast of Vietnam

1Laboratory of Ecology and Environmental Management, Science and Technology Advanced Institute, Van Lang University, Ho Chi Minh City, Vietnam 2Faculty of Applied Technology, School of Engineering and Technology, Van Lang University, Ho Chi Minh City, Vietnam 3Faculty of Chemistry-Biology-Environment, Pham Van Dong University, Quang Ngai City, 49000, Vietnam 4Biology Department, Hue University of Education, Hue University, 49000, Vietnam Article Information Received 10 November 2022 Revised 22 December 2022 Accepted 24 January 2023 Available online 22 May 2023 (early access)
STEM Research Trends From 2013 to 2022: A Systematic Literature Review

Integrasi pendekatan STEM (Science, Technology, Engineering and Mathematics) ke dalam pembelajaran terus menarik perhatian para peneliti dan akademisi. Guru memainkan peran kunci dalam keberhasilan dan dukungan pembelajaran ketika menerapkan pembelajaran berbasis STEM. Studi ini bertujuan untuk memberikan gambaran yang komprehensif, membangun literatur sebelumnya, dan untuk memberikan arah masa depan untuk penelitian STEM lebih lanjut oleh para peneliti dan pendidik. Ada 193 dokumen yang berisi STEM-nya di database Taylor Francis, yang disintesis. Pertanyaan penelitian mencakup frekuensi publikasi tahunan. Distribusi mencakup judul STEM, distribusi metode dan topik, jumlah yang paling banyak dikutip, sebagian besar negara yang berkontribusi, dan jurnal yang sering diterbitkan di bidang STEM. Dari 193 pasal, hanya 21 yang memuat kata STEM pada judulnya, dan 64 dokumen melihat peningkatan yang signifikan dalam frekuensi publikasi pada tahun 2022. Sebagian besar penelitian yang diterbitkan di bidang STEM berfokus pada pengajaran dan pembelajaran serta penguasaan konsep. Diurutkan berdasarkan negara, Amerika Serikat, Inggris, dan Swedia memberikan kontribusi terbesar di bidang ini dibandingkan negara lain, diikuti oleh Belanda, Jerman, Finlandia, dan Norwegia. Penulis yang paling banyak dikutip adalah Joseph Krajcik, Susan Codere, Chanyah Dahsah, Renee Bayer, dan Kongju Mun, yang telah dikutip sebanyak 110 kali. Berdasarkan jumlah artikelnya, International Journal of Science Education merupakan jurnal yang paling banyak berkontribusi pada STEM antara tahun 2013 hingga 2022. Amerika Serikat, Inggris Raya, dan Swedia memberikan kontribusi terbesar di bidang ini dibandingkan dengan negara lain, diikuti oleh Belanda, Jerman, Finlandia, dan Norwegia. Penulis yang paling banyak dikutip adalah Joseph Krajcik, Susan Codere, Chanyah Dahsah, Renee Bayer, dan Kongju Mun, yang telah dikutip sebanyak 110 kali. Berdasarkan jumlah artikelnya, International Journal of Science Education merupakan jurnal yang paling banyak berkontribusi pada STEM antara tahun 2013 hingga 2022. Amerika Serikat, Inggris Raya, dan Swedia memberikan kontribusi terbesar di bidang ini dibandingkan dengan negara lain, diikuti oleh Belanda, Jerman, Finlandia, dan Norwegia. Penulis yang paling banyak dikutip adalah Joseph Krajcik, Susan Codere, Chanyah Dahsah, Renee Bayer, dan Kongju Mun, yang telah dikutip sebanyak 110 kali. Berdasarkan jumlah artikelnya, International Journal of Science Education merupakan jurnal yang paling banyak berkontribusi pada STEM antara tahun 2013 hingga 2022.
The Fitting of a Generalization of the Logistic Curve

Special cases were originally proposed by Putter [1920] for various types of animal growth (see e.g. von Bertalanffy [1957]), and recently Richards [1959] has exemplified the general form of the curves and suggested that they may be useful for the empirical description of plant growth. For further details of the history of these curves and their mathematical properties reference should be made to Richards' paper. It suffices to say here that the family defined by (1) includes as special cases several curves which have been used empirically for the description of growth, including the 'monomolecular' (diminishing returns) curve (6 = -1), the exponential curve (6 -> 0 through positive values), the logistic curve (6 = 1), and the Gompertz curve (6 a) with A fixed and K a linear function of 0).
Rank-based process control for mixed-type data

ABSTRACT Conventional statistical process control tools target either continuous or categorical data but seldom both at the same time. However, mixed-type data consisting of both continuous and categorical observations are becoming more common in modern manufacturing processes and service management. However, they cannot be analyzed using traditional methods. By assuming that there is a latent continuous variable that determines the attribute levels of a categorical variable, the ordinal information among the attribute levels can be exploited. This enables us to simultaneously describe and monitor continuous and categorical data in a unified framework of standardized ranks, based on which a multivariate exponentially weighted moving average control chart is proposed. This control chart specializes in detecting location shifts in continuous data and in latent continuous distributions of categorical data. Numerical simulations show that our proposed chart can efficiently detect location shifts and is robust to various distributions.
Python-Based Circuit Design for Fundamental Building Blocks of Spiking Neural Network

Spiking neural networks (SNNs) are considered a crucial research direction to address the “storage wall” and “power wall” challenges faced by traditional artificial intelligence computing. However, developing SNN chips based on CMOS (complementary metal oxide semiconductor) circuits remains a challenge. Although memristor process technology is the best alternative to synapses, it is still undergoing refinement. In this study, a novel approach is proposed that employs tools to automatically generate HDL (hardware description language) code for constructing neuron and memristor circuits after using Python to describe the neuron and memristor models. Based on this approach, HR (Hindmash–Rose), LIF (leaky integrate-and-fire), and IZ (Izhikevich) neuron circuits, as well as HP, EG (enhanced generalized), and TB (the behavioral threshold bipolar) memristor circuits are designed to construct the most basic connection of a SNN: the neuron–memristor–neuron circuit that satisfies the STDP (spike-timing-dependent-plasticity) learning rule. Through simulation experiments and FPGA (field programmable gate array) prototype verification, it is confirmed that the IZ and LIF circuits are suitable as neurons in SNNs, while the X variables of the EG memristor model serve as characteristic synaptic weights. The EG memristor circuits best satisfy the STDP learning rule and are suitable as synapses in SNNs. In comparison to previous works on hardware spiking neurons, the proposed method needed fewer area resources for creating spiking neurons models on FPGA. The proposed SNN basic components design method, and the resulting circuits, are beneficial for architectural exploration and hardware–software co-design of SNN chips.
Comparison between Milgram’s and Niven’s Obedience Theory on Nurses in Obedience using Personal Protective Equipment

Personal protective equipment (PPE) is a protection tool from potential hazards in the workplace. Low nurse obedience to using PPE at hospitals can increase the occurrence of work accidents. Nurse obedience to using PPE can be seen from the external factors suggested in Milgram's theory and internal factors explained in Niven's theory. This study aimed to compare nurse obedience to using PPE through the analyses of Milgram ’ s and Niven's theories. This study was an observational study with a cross-sectional study design. The population of this study was 187 nurses in the inpatient installation of Dr. R. Sosodoro Djatikoesoemo Bojonegoro Hospital. A sample of 113 nurses were then selected to be the respondents. The influence test was performed using linear regression. Based on Milgram's theory, external factors were more dominant in controlling obedience to using PPE. The external factors that had a significant effect included location status, proximity to authority figures, and the legitimacy of authority figures. Meanwhile, Niven's theory showed only one internal factor, understanding instruction significantly influenced nurse obedience to using PPE. Therefore, it is recommended to formulate regulations and a more binding system through rewards and punishment to increase nurse obedience
Flexibility Calculation of Like-U Type Flexure Hinge

A new like-U type flexure hinge structure is provided, based on Castigliano's second theorem and calculus theory, taking the centrifugal angle parameters as the integration variable, and defining the intermediate parameters, it deduces the analytic computational formula for the like-U type flexure hinge flexibility. By changing the structural parameter of the flexure hinge, it is able to transform four different structure flexure hinges, and the deduced analytic computation formula can be applied to all of these four structures flexure hinges. After analyzed twelve flexure hinges of different structures by applying finite-element method, it is found that the results are in good agreement with the results of analytic computation formula; thus verify the validity of the analytic computation formula, realize accurate design and computation for such flexure hinges, and provide the theoretical base for technical application of like-U type flexure hinge.
A weakly informative prior for Bayesian dynamic model selection in fMRI

Bayesian dynamic methods for studying the complexity of the brain is an area of active research. Functional magnetic resonance imagining (fMRI) is an important tool to determine which parts of the brain are activated by different types of physical behavior. Due to the nature of fMRI data with high frequency behavior, Bayesian dynamic models for identifying sparsity are indeed of far-reaching. Therefore in this work, we propose a new weakly-informative prior for the state variances producing one-step-ahead proper estimations and inducing shrinkage in the fMRI sparse-data. In order to use model selection in a fully automatic framework, we describe the coupling or lead-lag between any pair of brain regions using a mixture of prior distribution for the connectivity parameters. To explore the performance of the approach we consider a simulation study and apply the proposal to a real functional magnetic resonance imaging data set.
Identification of ZmBK2 Gene Variation Involved in Regulating Maize Brittleness

Maize stalk strength is a crucial agronomic trait that affects lodging resistance. We used map-based cloning and allelic tests to identify a maize mutant associated with decreased stalk strength and confirmed that the mutated gene, ZmBK2, is a homolog of Arabidopsis AtCOBL4, which encodes a COBRA-like glycosylphosphatidylinositol (GPI)-anchored protein. The bk2 mutant exhibited lower cellulose content and whole-plant brittleness. Microscopic observations showed that sclerenchymatous cells were reduced in number and had thinner cell walls, suggesting that ZmBK2 affects the development of cell walls. Transcriptome sequencing of differentially expressed genes in the leaves and stalks revealed substantial changes in the genes associated with cell wall development. We constructed a cell wall regulatory network using these differentially expressed genes, which revealed that abnormal cellulose synthesis may be a reason for brittleness. These results reinforce our understanding of cell wall development and provide a foundation for studying the mechanisms underlying maize lodging resistance.
Handbook of Mathematical Functions with Formulas, Graphs,

The DLMF, also being published as a book, is the successor to Abramowitz and Stegun's NBS Handbook of Mathematical Functions with Formulas, Graphs. Handbook of Mathematical Functions has 24 ratings and 2 reviews. Douglas said: Even in the days of Mathematica, which I've used for over 10 years, I stil. Abramowitz, M. and Stegun, I. A. : Handbook of mathematical functions with formulas, graphs, and mathematical tables. National Bureau of Standards Applied.
qLPV modeling and mixed-sensitivity L 2 control for a magnetic levitation system

ABSTRACT This paper proposes a comprehensive mixed-sensitivity control design for an experimental magnetic levitation (Maglev) system. The control strategy can be seen as an extension of the loop-shaping procedure for discrete-time linear parameter-varying (LPV) systems using linear-fractional representation (LFR). By making use of an efficient quadratic approach given in the form of linear matrix inequalities (LMIs), a functional and computationally attractive gain-scheduling technique is achieved. Despite the rigorous mathematical considerations to obtain the controller, the guidelines to its practical implementation are presented as a straightforward method using LMIs. A detailed modeling of the Maglev plant manufactured by Quanser is carried out to illustrate the procedure, including a description of the nonlinear equations embedding process to obtain a discretized quasi-LPV (qLPV) model. Experimental results demonstrate the effectiveness of the proposed control design.
Friction, wear, and characterization of magnesium composite for automotive brake pad material

Magnesium metal matrix composites for lightweight brake pad applications are developed in this study. The composites are fabricated by using the powder metallurgy process. The addition of 0.5 wt. % to 2 wt. % Y2O3 (Rare Earth Oxide) used as a reinforcement to the AZ31 Mg composite is investigated. Density, hardness, and tribometer tests are carried out according to the ASTM standards. The friction and wear test of magnesium composites is tested against the grey cast iron disc. FESEM analysis shows the microstructure and morphology of worn surfaces. The elemental mapping result depicts that the elements of Mg, Al, Zn, Y, and O are uniformly distributed in the composite. X-ray diffraction analysis shows the compounds of Y2O3, MgO, ZnO, and Al2O4 are present on the worn surface of AZ31 + 2 wt. % Y2O3 composite. The outcome of the experiment reveals that increasing the proportion of yttrium oxide increases the magnesium composite's density and decreases the porosity. AZ31 + 2 wt. % Y2O3 composite exhibits the highest hardness of 122HV, a stable coefficient of friction, and a lower wear rate compared to AZ31 + 0 wt. % Y2O3 composite.
Influence of Molecular Properties of the Fluid on Simulation of the Total Heat and Mass Transfer of Solid Precipitation Particles.

Abstract Heat transfer measurements from a smooth and a rough (lobe structured) sphere to water (Prandtl number Pr = 7) at Reynolds numbers 3 × 103 < Re < 7.5 × 104 are described and compared to mass transfer measurements made previously under identical flow conditions but at Schmidt number Sc = 2170. The comparison shows how the molecular properties of the fluid affect the transfer of smooth and rough particles and, by inference, how the results of transfer measurements in liquids can be applied to air. The new measurements help to establish a safer basis for model experiments. They essentially confirm previously made extrapolations on the roughness effect on the convective heat and mass transfer of spherical hailstones.
Detrital Zircon Geochronology of the Volyn-Orsha Sedimentary Basin in Western Ukraine: Implications for the Meso-Neoproterozoic History of Baltica and Possible Link to Amazonia and the Grenvillian—Sveconorwegian—Sunsas Orogenic Belts

We used LA-ICP-MS U-Pb data for detrital zircon to constrain the Maximum Depositional Age (MDA) and provenance of clastic sedimentary rocks of the Volyn-Orsha sedimentary basin, which filled an elongated (~625 × 250 km) depression in SW Baltica and attained ~900 m in thickness. Eighty-six zircons out of one hundred and three yielded concordant dates, with most of them (86%) falling in the time interval between 1655 ± 3 and 1044 ± 16 Ma and clustering in two peaks at ca. 1630 and 1230 Ma. The remaining zircons yielded dates older than 1800 Ma. The MDA is defined by a tight group of three zircons with a weighted mean age of 1079 ± 8 Ma. This age corresponds to the time of a ~90° clockwise rotation of Baltica and the formation of the Grenvillian—Sveconorwegian—Sunsas orogenic belts. Subsidence was facilitated by the presence of eclogites derived from subducted oceanic crust. The sediments of the Orsha sub-basin in the northeastern part of the basin were derived from the local crystalline basement, whereas the sediments in the Volyn sub-basin, extending to the margin of Baltica, were transported from the orogen between Laurentia, Baltica and Amazonia.
ADVANCES IN GLOBAL OPTIMISATION FOR SPACE TRAJECTORY DESIGN

AbstractWe describe, in the framework of global optimi-sation, four trajectory optimisation problems, rep-resentative of three di erent important typologiesoften encountered in space mission design. Af-ter giving a brief description of the astrodynam-ical details necessary to implement the problemswe solve them by applying Di erential Evolutionand Multiple Particle Swarm Optimisation keep-ing the number of objective function evaluationsto a minimal amount to ensure low computationaltimes. We show how these techniques may be use-fullyexploitedtoperformfastoptimisationsgetting rst estimates of relevant mission design param-eters thus helping to take early decisions on theoverall spacecraft design.1 IntroductionFinding the best way to transfer a spacecraft be-tween planets or orbits is a complex problem. Thetraditional methodologies used to design the space-craft trajectories have evolved, in the last years,by taking advantage of a number of emerging newtechniques that promise to radically simplify thetask of nding optimal solutions [2]. The principaltheoretical step that has to be taken in order to un-derstandmanyofthenewapproachesisthatofcon-sidering the trajectory design problem as a globaloptimisation problem. While this does not changethe issue in its nature, it allows to account for thecomplex topology of the search spaces commonlyencountered. Known issues limiting the eciencyof the variousmethods arethe numberof localmin-
Flat optics with cholesteric and blue phase liquid crystals

ABSTRACT The cholesteric (Ch) phase is an ancient liquid crystal (LC) phase, with its roots dating back to the days of Friedrich Reinitzer. It is most well known for its ability to selectively reflect circularly polarised light with the same rotation handedness as the helical structure, and have found applications in polarising and display devices. Most studies to date utilising the reflective properties of ChLCs, however, have treated ChLCs as simple dielectric mirrors in which light follows the law of reflection. We have recently shown that through controlling the phase of the Ch helix, it is possible to control the phase of reflected light. Because the phase can be controlled over 0–2π, the reflected wavefront from a planar device can be designed to possess non-specular properties, such as deflection and lensing. In this paper, we aim to provide a comprehensive understanding of the phenomenon by presenting theoretical and experimental results on the dependence of the reflected light phase on the helix phase, and the effect of chiral handedness on the phenomenon. Also, we show that wavefront manipulation based on the same concept can be achieved in Ch blue phases (BPs), which are chiral LCs with three-dimensional periodicity. GRAPHICAL ABSTRACT
Low Serum IL-18 Levels May Predict the Effectiveness of Dupilumab in Severe Asthma

Objective Dupilumab, a monoclonal antibody specific for the human interleukin (IL)-4 receptor α, is used to treat severe asthma, especially in patients with elevated blood eosinophil counts and fractional exhaled nitric oxide (FeNO). The therapeutic response to dupilumab is highly variable. In this study, we explored new serum biomarkers to accurately predict the effect of dupilumab and examine the effect of dupilumab based on changes in the clinical parameters and cytokine levels. Methods Seventeen patients with severe asthma treated with dupilumab were enrolled. Responders, defined as those with a ＞0.5-point decrease in the Asthma Control Questionnaire (ACQ) score after 6 months of treatment, were included. Results There were 10 responders and 7 non-responders. Serum type 2 cytokines were equivalent between responders and non-responders; the baseline serum IL-18 level was significantly lower in responders than in non-responders (responders, 194.9±51.0 pg/mL; non-responders, 323.4±122.7 pg/mL, p=0.013). The cut-off value of IL-18 at 230.5 pg/mL could be used to distinguish non-responders from responders (sensitivity 71.4, specificity 80.0, p=0.032). Conclusion A low baseline serum IL-18 level may be a useful predictor of an unfavorable response to dupilumab in terms of the ACQ-6.