Miracle-dz/UniFAR-FTUs huggingface dataset:
Not ‘just consumers of content’: early insights into the policy enactment of the Digital Learning Framework

ABSTRACT In Ireland, as with many international jurisdictions, digital technology is firmly positioned at the core of educational discourses. However, despite a rise in ‘techno-positivity’ among professionals in schools, these positive attitudes do not seem to permeate through to practice nor in effective learning outcomes. As a result, given the introduction of the Digital Learning Framework in the Irish schooling system, this study focuses on the initial experiences of those who lead the initiative within their respective schools and the contextual nuances they must navigate in the design of the enactment. This qualitative study comprised in-depth interviews with the Digital Learning Leaders of 10 different schools. Data evidenced the initial organisational considerations a leader must reckon with during the planning phase, and early indications of pedagogical impact, leading to a conclusion regarding contextual literacy. The research also highlights the subtle policy shift of embedding digital technologies within school evaluation mechanisms, heightening a sense of accountability associated with successful enactment.
Theoretical Study on the Photoemission Performance of a Transmission Mode In0.15Ga0.85As Photocathode in the Near-Infrared Region

Benefiting from a high quantum efficiency, low thermal emittance, and large absorption coefficient, InxGa1−xAs is an excellent group III–V compound for negative electron affinity (NEA) photocathodes. As the emission layer, InxGa1−xAs, where x = 0.15, has the optimal performance for detection in the near-infrared (NIR) region. Herein, an NEA In0.15Ga0. 85As photocathode with Al0.63Ga0. 37As as the buffer layer is designed in the form of a transmission mode module. The electronic band structures and optical properties of In0.15Ga0. 85As and Al0.63Ga0. 37As are calculated based on density functional theory. The time response characteristics of the In0.15Ga0. 85As photocathode have been fully investigated by changing the photoelectron diffusion coefficient, the interface recombination velocity, and the thickness of the emission layer. Our results demonstrate that the response time of the In0.15Ga0. 85As photocathode can be reduced to 6.1 ps with an incident wavelength of 1064 nm. The quantum efficiency of the In0.15Ga0. 85As photocathode is simulated by taking into account multilayer optical thin film theory. The results indicate that a high quantum efficiency can be obtained by parameter optimization of the emission layer. This paper provides significant theoretical support for the applications of semiconductor photocathodes in the near-infrared region, especially for the study of ultrafast responses in the photoemission process.
Vortex spin-torque oscillator using Co 2 Fe x Mn 1 -x Si Heusler alloys

We show spin-transfer-torque-driven vortex oscillations in current-perpendicular-to-plane giant magnetoresistance junctions using epitaxially grown ${\mathrm{Co}}_{2}{\mathrm{Fe}}_{x}{\mathrm{Mn}}_{1\ensuremath{-}x}\mathrm{Si}$ (CFMS) Heusler alloy thin films. The soft magnetic property and high spin polarization of CFMS enable us to realize vortex oscillation emitting large microwave power with a low threshold current. The output power is maximized for a certain Fe-Mn composition ratio associated with a reduction of the threshold current for the oscillation, which is in agreement with a general model for spin-torque oscillation. Through comparison with an analytical theory that describes the translational motion of a vortex core, we show that the vortex core motion excited in the present device is inhomogeneous along the thickness direction. In spite of the inhomogeneity, the gyration radius at the CFMS/spacer interface region was estimated to be $\ensuremath{\sim}75%$ of the actual ferromagnetic layer radius, which indicates that the CFMS-based all-metallic junction is useful for achieving large-amplitude vortex core motion. This comprehensive investigation would also be useful for designing high-performance all-metallic nano-oscillators based on magnetic vortex dynamics.
The Effectiveness of Butterfly Hug in Reducing Anxiety Long-Distance Relationship (LDR) with Parents in Nursing Students

Introduction: Anxiety related to a long-distance relationship with parents is an unpleasant emotional reaction when away from parents that can cognitively interfere with feelings and emotions caused by feelings of loneliness and longing for home. One of the ways to reduce anxiety is a butterfly hug. Methods Using quasi-experimental with the control group and pre-posttest design. The sampling technique used purposive sampling. The sample consisted of 60 respondents divided into a control group of 30 respondents and an intervention group of 30 respondents. Using the Zung Self-Anxiety Rating Scale for the instrument. The intervention group received a butterfly hug for 6 days in 8 sessions every day, and the control group received music therapy for 6 days. Bivariate analysis used the parametric test paired sample t-test to see the difference between the prepost-test intervention group and to see the difference between the prepost-test control group on the anxiety level using the nonparametric Wilcoxon test. Analysis of bivariate test to see the difference between groups using the independent sample t-test. Result: The results of the Wilcoxon test of the anxiety level control group p=0,274 (p=>0,05), meanwhile the results of the intervention group of the paired sample t-test intervention group there was a significant effect (p=0,000). The results of the independent sample t-test between the control and intervention groups were p=0,001 (p=<0,05). Conclusions: Butterfly hug therapy is an effective therapy to reduce anxiety in LDR with parents in nursing students. This therapy is expected to be applied and used as an intervention to reduce anxiety.
FDTD BASED DICTIONARY MATRIX FOR SPARSITY-BASED THROUGH-WALL RADAR IMAGING

Compressive sensing for through-wall radar imaging (TWRI) is a promising method to obtain a high-resolution image with limited number of measurements. The capability of the existing method in the framework of CS is limited due to the model error stemmed from the approximated signal model which does not consider multipath returns or only consider first-order interior wall multipath returns. In order to exploit various multipath returns, finite-difference time domain (FDTD) technique is used to obtain the scattered signal for each assumed target position and then to construct the exact forward scattering model. Then, sparse reconstruction is used to solve this linear inverse problem. Numerical results demonstrate that the proposed approach performs better at ghost suppression in the same condition of the signal-to-noise ratio (SNR).
Diagnostic methods to measure spastic segment and guide tailored myotomy length in type 3 achalasia

Myotomy length in type 3 achalasia is generally tailored based on segment of spasticity on high‐resolution manometry (HRM). Potential of length of tertiary contractions on barium esophagram (BE) or length of thickened circular muscle on endoscopic ultrasound (EUS) to guide tailored myotomy is less understood. This study aimed to assess agreement between spastic segments lengths on HRM, BE, and EUS among patients with type 3 achalasia.
Simultaneous identification of convection velocity and source strength in a convection–diffusion equation

In this work we are concerned with the analysis on a simultaneous finite element reconstruction of the convection velocity and source strength in a time-dependent convection–diffusion equation. The ill-posed problem is formulated into an output least-squares nonlinear minimization by an appropriately selected Tikhonov regularization. The regularizing effect and mathematical properties of the regularized system are justified and demonstrated. The nonlinear optimization problem is approximated by a fully discrete finite element method, whose convergence is rigorously established.
A novel interpolation method of HRTFs based on the common-acoustical-pole and zero model

For control of sound localization, synthesis of Head-Related Transfer Functions (HRTFs) is an important technique. Because HRTFs vary as a function of source location and show large inter-subject variation, systems based on HRTF synthesis should have HRTFs for each listener covering the entire area around the listener. However, it is not practical to obtain them through measurement. One possible solution to this problem is to interpolate measured HRTFs to obtain those for intermediate directions. This study investigates a new interpolation method based on an effective modeling method of HRTFs called the Common-Acoustical-Pole and Zero (CAPZ) model. This model represents measured HRTFs with poles, which are assumed to be independent of all source directions, and zeros, which depend on the source direction. Interpolation of HRTFs is achieved by interpolating MA coefficients corresponding to the zeros. Results show that the proposed method can reduce the necessary data size for a set of HRTFs while retaining the same accuracy as those obtained with conventional methods that use linear interpolation of the impulse responses and magnitude responses. Under the conditions reported in this paper, the data size was reduced to about 30% of the data size obtained with conventional methods.
Synthesis of a phosphorus and triazole-containing compound and its enhancement on flame retardancy and mechanical properties of an epoxy resin

A high effective P/N-containing flame retardant additive CDD was triumphantly synthesized with nitrogen-rich 3,5-Diamino-1,2,4-triazole, DOPO and cinnamaldehyde. With the help of 4 wt% CDD, Epoxy resin (EP) sample succeeded in UL-94 V-0 test, and improved its LOI value to 33.5%. EP/4 wt%CDD sample also performed very well in cone calorimeter (CC) test. For example, the peak of heat release rate of EP/4 wt%CDD decreased to 603 kW/m2, which was 56.8% of EP sample without flame retardants. All these details showed that CDD was highly effective in fire resistance. Besides, the addition of CDD also drastically improved mechanical strength of EP. Tensile strength, flexural strength and izod iMPact strength of EP/4 wt%CDD sample was increased to 102 MPa, 124 MPa and 38 kJ m−2, which was 118.6%, 129.2% and 126.7% of control group. At last, the flame-retardant mechanism of CDD was studied by FTIR, XPS, Raman spectra, and SEM. The results showed that CDD’s perfect performance in fire resistance was ascribed to the generation of phosphorus-rich char layer in condensed phase.
Cross Correlation-Based Ultrasonic Gas Flow Sensor With Temperature Compensation

In this article, the design of an ultrasonic gas flow sensor with a low cost and low energy temperature compensation method based on time of flight (ToF) measurement is presented. In order to minimize the cost, the proposed thermal compensation method, on the one hand, does not require a temperature sensor and, on the other hand, only requires an initial calibration at room temperature. The presented commercial off the shelf (COTS)-based sensor has been previously optimized at different levels: mechanical design, validation of the piezoelectric transducers, and selection of the ToF detection algorithm. As a result, this article presents a gas flow sensor based on a V-configuration pipe, using 200-kHz piezoelectric transducers and a cross correlation method based on the Hilbert transform (HT). The proposed design fully meets the accuracy requirements given by the EN14236 standard, improving the features of current commercial gas flow sensors in terms of cost, accuracy, and power consumption.
Search for Axions with Micromegas Detectors in the CERN CAST Experiment

SEARCH FOR AXIONS WITH MICROMEGAS DETECTORS IN THE CERN CAST EXPERIMENT The CAST experiment is searching for the axion, which is a light, weakly interacting pseudoscalar particle, that is proposed to solve the so called Strong Charge-Parity Problem. The axions CAST is looking for are produced from photons in the solar core and CAST aims to convert them back into photons in a superconducting LHC dipole magnet and detect the photons in the x-ray detectors attached to ends of each magnet bore. CAST uses three micromegas and a CCD detector and can track the Sun during sunset and sunrise. The two of the micromegas take tracking data during the sunset solar tracking, and were used for the first time in 2008. The analysis of the data taken in 2008 with these two detectors show no signal of axions, and new upper limits on the axion mass-coupling constant parameter space are established due to sensitivity of detectors for the axion mass range of 0.38eV to 0.65eV.
YouTube Users' Behavioral Responses towards Musical Ads (A Comparative Study vs Voice Over ads)

: Digital advertising depends mainly on what the user sees and hears, and since the use of appropriate music may form a link be-tween the user and the company. Advertising and media agencies spend billions annually on advertising music and melodies, as they have an influential role in achieving the desired effect. The music and melodies make it easier for the user to remember the ad, enhance memory and serving as a mnemonic device. However, there is a gap in research studies on the influence of music or song in the advertisement on YouTube user behavior is not handled. This current study provides a new angle to examination in the field of music advertising (advertising in the form of a song), taking into account the users’ experience of the interaction between the song’s music, visual scenes, and words in the lyrical (musical) advertisements verses the video advertisement accompanying the audio narration (Voice over). The research adopts the experimental approach by designing three YouTube advertisement (Musical ad-two type of Voice over ads). The research result came to that there is statistically significant difference between the first adver - tisement, the second and the third one in the advantage of the first advertisement - the musical ad (the song).
Genetic evaluation of 50 Turkish patients with neurofibromatosis type 1: 2 years experience of a single center

Neurofibromatosis type 1 is an autosomal dominant neurocutaneous disorder. Clinical diagnosis is difficult in early childhood, and it is possible to miss a critical interval for tumour screening. In this study, we aimed to characterize the mutational spectrum of Turkish patients and discuss the benefits of molecular testing.
Learning rate schedules for stochastic gradient algorithms

Stochastic gradient descent is an important class of stochastic processes which is relevant to learning as studied in engineering and biology. LMS adaptive filtering, online backpropagation, and forms of k-means clustering (vector quantization), all important signal processing algorithms, are stochastic gradient descent processes. Stochastic gradient processes can often be viewed as online optimization algorithms. The advantage of these algorithms is that the update complexity is typically linear in the number of system parameters as compared to quadratic or worse for variants of Newton's method. Thus there continues to be great interest in using stochastic gradient algorithms to solve the large least squares problems which are ubiquitous in engineering. Each algorithm takes steps down the gradient of some loss function. The step size is controlled by an adjustable sequence of gains (or "learning rate schedule"). How to choose this sequence in order to quickly find a good local minimum of the loss is the central problem studied in this work. We present a new deterministic schedule which has improved chances of escaping from local minima but which is still capable of achieving fast convergence asymptotically. These schedules keep the learning rate constant at small times (the "search" phase), and reduce the rate like c/t asymptotically (the "converge" phase). This schedule performs much better than the standard choice for k-means clustering. We propose a new adaptive learning rate schedule, based on our extensions to stochastic approximation theory, which tunes c on line. Our starting point is the classical result that in order to converge to a minimum as quickly as possible, the learning rate must go asymptotically as c/t, where c is greater than some task-dependent threshold. We develop a specific, computationally inexpensive method for determining whether a particular c is large enough and prove that it works. Additionally, experimental results on signal processing tasks are presented for both new schedules.
Optimizing the photon selection of the CMS Single-Photon search for Supersymmetry using multivariate analyses

The purpose of this thesis is to improve the photon selection of the CMS SinglePhoton search for Supersymmetry by using multivariate analyses. The Single-Photon search aims to find Supersymmetry (SUSY) in data taken by the Compact Muon Solenoid (CMS) detector at the Large Hadron Collider located at the research center CERN. SUSY is an extension of the standard model of particle physics. The search is designed for a general gauge mediation scenario, which describes the gauge mediated SUSY breaking. The analysis uses final states with jets, at least one photon and missing transverse energy. A data-driven prediction of the multijet background is performed for the analysis. For this purpose, photon candidates have to be classified into two selections. In this thesis the usage of multivariate analyses for the photon candidate classification is studied. The methods used are Fisher Discriminant, Boosted Decision Trees and Artificial Neural Networks. Their performance is evaluated with respect to different aspects important for the Single-Photon search and they are compared to the analysis’ current selection method. It is found, that the studied approaches offer some advantages like an increased photon identification efficiency, a reduced statistical background uncertainty and a larger flexibility in the choice of the background control region. Übersicht Das Ziel dieser Arbeit ist die Verbesserung der Photon-Selektion der CMS SinglePhoton Suche nach Supersymmetrie unter Verwendung Multivariater Analysen. Das Ziel der Single-Photon Suche ist es, Supersymmetrie (SUSY) in Daten, aufgenommen vom Compact Muon Solenoid (CMS) Detektor am Large Hadron Collider am Forschungszentrum CERN, zu entdecken. SUSY ist eine Erweiterung des Standardmodells der Teilchenphysik. Die Suche ist auf ein „general gauge mediation“ Szenario ausgelegt, das die Symmetriebrechung beschreibt („gauge mediated SUSY breaking“). Die Analyse nutzt Endzustände mit Jets, mindestens einem Photon und fehlender Transversalenergie. Eine datengestützte Vorhersage des Multijet-Untergrunds wird für die Analyse durchgeführt. Zu diesem Zweck müssen Photonkandidaten in zwei Klassen eingeteilt werden. In dieser Arbeit wird die Verwendung Multivariater Analysen zur Klassifikation der Photonkandidaten untersucht. Die benutzten Verfahren sind Fisher Diskriminante, Boosted Decision Trees und Künstliche Neuronale Netze. Die Ergebnisse ihrer Anwendung werden bezüglich unterschiedlicher Aspekte, die für die Single-Photon Suche wichtig sind, untersucht und mit der bisherigen Photon-Selektion verglichen. Es stellt sich heraus, dass die untersuchten Verfahren einige Vorteile bieten, wie eine erhöhte Photon-Identifikationseffizienz, eine reduzierte statistische Untergrundunsicherheit und eine größere Flexibilität bei der Wahl der Untergrund-Kontrollregion.
Polymer network liquid crystal grating/Fresnel lens fabricated by holography

ABSTRACT In this article, polymer network liquid crystal (PNLC) grating/Fresnel lens is fabricated by holography. The exposure light pattern for the grating is obtained by interfering two planar wave fronts, while the Fresnel pattern is achieved by interfering a planar wave front and a spherical wave front. Owing to the alignment effect and anchoring power of polymer network, the holographic PNLC grating achieves improved diffraction efficiency, and remarkably reduced operation voltage (reduced by 80%) compared with holographic polymer-dispersed-liquid-crystal and holographic polymer-stabilised blue-phase liquid-crystal gratings, while maintaining submillisecond response. Moreover, it achieves high spatial frequency with a 2-μm grating period, thanks to the holographic fabrication. The holographic PNLC Fresnel lens also exhibits attractive electro-optical properties. Graphical Abstract
Consumption of Cassava Extract (Manihot Esculenta) Improves Pancreatic Histology and Seminiferous Tubules in Wistar Rats Induced Diabetes Mellitus with Streptozotocin

Diabetes Mellitus (DM) can damage various organs, which are the pancreas and the testes, which cause infertility. Therefore, alternative treatment is needed, including cassava (Manihot Esculenta) which contains polyphenol antioxidants that can reduce free radicals caused by hyperglycemia. The objectives of the study were to determine the effect of cassava consumption on the histological pancreas and testes of Wistar rats induced with streptozotocin. This study was an experimental study posttest only control group design. Experimental animals were divided into four treatment groups, namely healthy controls (K1), DM aqua dest (K2), DM metformin (K3), and DM cassava (K4). The treatment was given after successful DM induction. The histology of the pancreas was the area of the islets of Langerhans. The histology of the testes was the thickness of the seminiferous tubule epithelium. The analysis used a one-way ANOVA test. The average area of Langerhans Island, respectively, namely 6482,95±117.71 µ m2, 2597.49±137.25 µ m2, 2746.93± 172.07 µ m2, and 3307.00 ± 368.51 µ m2 (p-value = 0.000). The mean epithelial thickness of the seminiferous tubules was 19.62±1.12 µm, 15.59 ±0. 46µm, 17.05±1. 42µm, and 18.09±0. 52µm (K4) (p-value = 0.000). In conclusion, the consumption of cassava extract (Manihot esculenta) can improve the histological picture of the pancreas and increase the thickness of the seminiferous tubule.
Multiple plant identifier via adaptive LMS convex combination

The least mean square (LMS) algorithm has become a very popular algorithm for adaptive filtering due to its robustness and simplicity. A difficulty concerning LMS filters is their inherent compromise between tracking capabilities and precision, that is imposed by the selection of a fixed value for the adaption step. An adaptive convex combination of one fast LMS filter (high adaption step) and one slow LMS filter (low adaption step) was proposed as a way to break this balance. We propose to generalize this idea, combining multiple LMS filters with different adaption steps. Additional speeding up procedures are necessary to improve the performance of the basic scheme. Some simulation work has been carried out to show the appropriateness of this approach when identifying plants that vary at different rates.