Miracle-dz/UniFAR-FTUs huggingface dataset:
Etkileşimli okuma etkinliklerinin yabancılara Türkçe öğretiminde yaratıcı yazma becerisine etkisi

Bu araştırmanın amacı, yabancı dil olarak Türkçe öğretiminde etkileşimli okuma etkinliklerinin yaratıcı yazma becerileri üzerindeki etkisini belirlemektir. Araştırma karma yöntem temel desenlerinden açıklayıcı sıralı tasarım ile yürütülmüştür. Araştırmanın nicel kapsamında ön ve son test kontrol gruplu deneysel desen, nitel kapsamında ise görüşme ve içerik analizi yöntemi uygulanmıştır. Araştırmanın deney (n=19) ve kontrol (n=19) grupları İstanbul Üniversitesi Dil Merkezi’nde B2 düzeyinde öğrenimine devam eden 38 öğrenciden oluşmaktadır. Araştırmanın nicel veri toplama aracını Beydemir ve Susar Kırmızı (2012) tarafından geliştirilmiş olan “Yaratıcı Yazma Ürünlerini Değerlendirme Ölçeği”, nitel veri toplama aracını ise yarı yapılandırılmış görüşme formu oluşturmaktadır. Elde edilen nicel veriler SPSS 26 programı, nitel veriler de içerik çözümleme yöntemi ile analiz edilmiştir. B2 kuru boyunca öğretim malzemesi olarak uzman görüşleri doğrultusunda seçilen özgün öyküler deney grubuna etkileşimli okuma etkinlikleri, kontrol grubuna ise standart okuma etkinlikleri ile uygulanmıştır. Araştırmanın nicel bulgularından elde edilen sonuçlara göre, öncelikle deney ve kontrol gruplarının her ikisinde de pozitif yönde anlamlı bir fark ortaya çıkmıştır. Ancak, grupların son testlerine ait puan ortalamaları istatiksel olarak karşılaştırıldığında deney grubunun lehine anlamlı bir fark bulunmuştur. Bu bulgular neticesinde, etkileşimli okuma etkinliklerinin uygulandığı deney grubundaki öğrencilerin, kontrol grubundaki öğrencilere kıyasla yaratıcı yazma becerisi kapsamında gelişimlerinin anlamlı bir şekilde daha fazla olduğu sonucuna ulaşılmıştır. Araştırmanın nitel bulgularından elde edilen sonuçlar, etkileşimli okuma yönteminin öğrencilere okuma sürecine aktif katılım, motivasyonun artması ve yaratıcılığın gelişmesi konularında katkı sağladığını göstermiştir. Araştırmanın nitel ve nicel bulguları birlikte değerlendirildiğinde, etkileşimli okuma etkinliklerinin yabancı dil olarak Türkçe öğrenen öğrencilerin yaratıcı yazma becerilerine olumlu yönde katkı sağladığı sonucunda varılmıştır.
Echelle++, a Fast Generic Spectrum Simulator

We present the software package, Echelle++, an open-source C++ code to simulate realistic raw spectra based on the Zemax model of any spectrograph, with a particular emphasis on cross-dispersed Échelle spectrographs. Echelle++ generates realistic spectra of astronomical and calibration sources, with accurate representation of optical aberrations, the shape of the point-spread function, detector characteristics, and photon noise. It produces high-fidelity spectra fast, a very important feature when testing data reduction pipelines with a large set of different input spectra, when making critical choices about order spacing in the design phase of the instrument, or while aligning the spectrograph during construction. Echelle++ also works with low-resolution, low signal-to-noise, multi-object, IFU, or long-slit spectra, for simulating a wide array of spectrographs. We chose to initially generate our own spectrograph model from the optical prescription in Zemax. Echelle++ can then be used independently, without access to commercial ray tracing software.
A Practical Guide to Variable Selection in Structural Equation Models with Regularized MIMIC Models

Methodological innovations have allowed researchers to consider increasingly sophisticated statistical models that are better in line with the complexities of real world behavioral data. However, despite these powerful new analytic approaches, sample sizes may not always be sufficiently large to deal with the increase in model complexity. This poses a difficult modeling scenario that entails large models with a comparably limited number of observations given the number of parameters. We here describe a particular strategy to overcoming this challenge, called regularization. Regularization, a method to penalize model complexity during estimation, has proven a viable option for estimating parameters in this small n, large p setting, but has so far mostly been used in linear regression models. Here we show how to integrate regularization within structural equation models, a popular analytic approach in psychology. We first describe the rationale behind regularization in regression contexts, and how it can be extended to regularized structural equation modeling (Jacobucci, Grimm, & McArdle, 2016). Our approach is evaluated through the use of a simulation study, showing that regularized SEM outperforms traditional SEM estimation methods in situations with a large number of predictors and small sample size. We illustrate the power of this approach in two empirical examples: modeling the neural determinants of visual short term memory, as well as identifying demographic correlates of stress, anxiety and depression. We illustrate the performance of the method and discuss practical aspects of modeling empirical data, and provide a step-by-step online tutorial. Materials. Materials used in the manuscript can be accessed here: https://osf.io/z2dtq/. Conflicts of Interest. The author(s) declare that they have no conflicts of interest with respect to the authorship or the publication of this article. Subjects. Ethical approval for the study was obtained from the Cambridgeshire 2 (now East of England-Cambridge Central) Research Ethics Committee (reference: 10/H0308/50) Prior Versions. The initial version of this manuscript was posted as a preprint here: https://psyarxiv.com/bxzjf/. Author Contributions. RJ, AMB, and RAK generated the idea for the study, the simulation specification, and wrote the manuscript. RJ ran the analyses while RJ, AMB, and RAK analyzed the results and generated the figures. All authors approved the final submitted version of the manuscript. Europe PMC Funders Group Author Manuscript Adv Methods Pract Psychol Sci. Author manuscript; available in PMC 2019 September 01. Published in final edited form as: Adv Methods Pract Psychol Sci. 2019 March 01; 2(1): 55–76. doi:10.1177/2515245919826527. E uope PM C Fuders A uhor M ancripts E uope PM C Fuders A uhor M ancripts
Minimal Energy Efficient Routing (MEER) Protocol using GSP For Sensor Network

The most important criterion while designing wireless sensor network is the consumption of energy[5,6,7]. There are many schemes cited for conservation of energy issues[1,2,8]. Again the efficient minimal energy consumption routing schemes are an important consideration. In this paper, we have proposed an energy saving scheme, named as minimal energy efficient routing (MEER) Protocol, which uses GSP (Gossip based sleep Protocol) to achieve energy efficiency in sensor networks. Here, we have compared our work with the existing work given by GSP[1] . We have shown the correctness & effectiveness of our protocol by mathematical simulation studies.
EFFECTS OF NON-PSYCHOTROPIC PHYTOCANNABINOIDS ON ORAL BACTERIA - IN VITRO STUDY

Jirásek P.1, Diabelko D.2, Růžička F.2, Storch J.3, Voborná I.1, Vacek J.4 1 Klinika zubního lékařství, Lékařská fakulta Univerzity Palackého v Olomouci, a Fakultní nemocnice Olomouc 2 Mikrobiologický ústav, Masarykova univerzita, Lékařská fakulta, a Fakultní nemocnice u sv. Anny v Brně 3 Oddělení pokročilých materiálů a organické syntézy, Ústav chemických procesů AV ČR, v. v. i. , Praha 4Ústav lékařské chemie a biochemie, Lékařská fakulta Univerzity Palackého v Olomouci
Compact dual-band circularly polarised antenna with omnidirectional and unidirectional properties

A novel dual-band circularly polarised (CP) antenna is presented in this study. The proposed antenna is composed of a U-slot patch and four sequentially rotated shorted monopoles. Different from conventional omnidirectional CP antennas with shorted monopolar patches, a novel capacitively coupled technique is proposed to achieve good impedance matching, which makes it possible to generate unidirectional CP patterns simultaneously. This antenna can generate omnidirectional CP radiation patterns in the global positioning system L1 band (1575 ± 5 MHz) for navigation application and unidirectional CP radiation patterns in the 2.4-GHz industrial, scientific, and medical band (2.40-2.48 GHz) for municipal wireless networks. The dual-band performance can be tuned separately. Experimental results confirm the good performances of a compact antenna with the size of 0.26 λ 0 × 0.26 λ 0 × 0.026 λ 0 . The obtained 10-dB impedance bandwidths can cover the two required bands. The 3-dB axial ratio (AR) bandwidths cover the lower band and the upper band from 2.425 to 2.46 GHz. In addition, a wide 3-dB AR beamwidth of 200° is obtained at 2.45 GHz. The simple structure and good performances make this antenna a good candidate for handheld devices and vehicular applications.
Integration of Derivative Control on SIPIC in Motor Speed Control

The proportional–integral–derivative (PID) controller is the most commonly used controller in control application due to its simplicity. However, the control output may exceed the plant input limit which eventually deteriorates the system performance. This is known as a windup phenomenon, which causes large overshoot, long settling time and instability in the control system. Various anti‐windup methods have been introduced to overcome the windup phenomenon such as the Steady‐State Integral Proportional‐Integral Controller (SIPIC). Due to the coupling of the proportional, integral and derivative tuning gains, it is difficult to tune for non‐overshoot and short settling time to coexist in a PID. With decoupling, a greater range of tuning gains can be applied to control the rising slope without disturbing the damping state. Currently, SIPIC with decoupling effect has only been studied for the proportional and integral tuning gains. This paper presents the effect of integrating derivative control on SIPIC in motor speed control. SIPIC+D shows better speed control on a direct current motor under no‐load and loading conditions compared with other existing anti‐windup added with derivative control.
Secure positioning technique based on encrypted visible light map for smart indoor service

Abstract. Indoor visible light (VL) positioning systems for smart indoor services are negatively affected by both cochannel interference from adjacent light sources and VL reception position irregularity in the three-dimensional (3-D) VL channel. A secure positioning methodology based on a two-dimensional (2-D) encrypted VL map is proposed, implemented in prototypes of the specific positioning system, and analyzed based on performance tests. The proposed positioning technique enhances the positioning performance by more than 21.7% compared to the conventional method in real VL positioning tests. Further, the pseudonoise code is found to be the optimal encryption key for secure VL positioning for this smart indoor service.
Details Matter

Social desirability is a tendency to respond to items in a socially acceptable way. It can bias results and is a threat to the validity of the measure. The current study focused on exploring the effect of different instructions on personality traits. The sample consists of 363 Slovak adults, 260 women, and 103 men. The participants were between 18 and 62 years old ( M = 25.6; SD = 6.76). The Big Five Inventory-2 was used for measuring personality traits and social desirability. The participants were split into two groups depending on which instruction was administered first – honest setting or social desirability inducing setting (imagining the selection situation). All participants responded to both scenarios. We hypothesized that extraversion, agreeableness, and conscientiousness are socially desirable traits, and so they will be higher using selection simulating instruction compared to honest instruction. The opposite was hypothesized for negative emotionality. The social desirability of open-mindedness was explored. The results confirmed all our hypotheses and showed that open-mindedness is a socially desirable trait as well. Importantly, we found an effect of the order of administrating different instructions – the effect of induced social desirability was present in the honest instruction setting.
Under-Actuated Nonholonomic Parallel Wrists

The introduction of nonholonomic constraints in parallel manipulators, in general, allows the reduction of the actuated-joint number without consistently affecting the reachable workspace. This principle is applied here to obtain new architectures of under-actuated parallel wrists. New hardware solutions are proposed for a nonholonomic spherical (nS) pair that was proposed in a previous paper. Then, this nonholonomic pair is used to generate ten novel architectures for under-actuated spherical wrists. Eventually, the controllability of the architectures with only one nS pair is demonstrated without resorting to the use of Lie brackets.
Impact of Refined Crude Oil Imports on Carbon Dioxide Emission (C02) in Nigeria

Purpose: The study investigated the impact of refined crude oil imports on carbon dioxide emission in Nigeria covering the period 1980 to 2020. Methodology: The study employed preliminary test of Augmented Dickey Fuller and Dickey-Fuller GLS unit root testing procedure while the main estimation technique is the Autoregressive Distributed Lag (ARDL). Data for the study is sourced from the World Bank’s development indicators and Central Bank of Nigeria statistical bulletin for various years. The dependent variable is carbon dioxide emission (CO2) while explanatory variables include refined oil imports (M), gross domestic product (Y) for economic growth, total factor productivity (TFP) for technological progress and innovation, oil price (OP) and nominal exchange rate (EXR). Findings: Findings in the study show that the contribution of refined oil imports to carbon dioxide emission is positively signed and statistically significant at 5 percent level in both long run and short run. There exists a unidirectional causation between oil import, and carbon dioxide emission. The study concludes that the positive values of refined oil imports pose serious environmental threat given the rise in carbon dioxide emission. Unique Contribution to Theory, Policy and Practice: The study therefore, recommends amongst others that the policymakers particularly the Nigeria’s executive arm of government need to diversify the economy from oil-based to non-oil based. Also, the country’s refineries should be de-regulated to reduce the over dependency on the importation of the refined crude oil imports alongside with the establishment of Government Agencies that will strictly monitor the refined crude oil production process which will go a long way in reducing the over reliance on refined crude oil importation as well as the environmental challenges emanating from refined oil consumption.
CONTENT VARIATIONS OF CARBAMAZEPINE TABLETS IN IRAQI COMMUNITY PHARMACIES: APPLICATION OF HIGH-PERFORMANCE LIQUID CHROMATOGRAPHY ASSAY METHOD

Objective: There is paucity in the literature and documentation regarding the post-marketing product quality in Iraq and Middle East countries in general. Therefore, a simple reverse phase high-performance liquid chromatography (RP-HPLC) method was developed and validated for the determination of carbamazepine (CMZ) content in post-marketed tablet dosage form. Methods: The RP-HPLC analysis was run at a flow rate of 1 ml/min with a mixture of methanol: water (70:30) mobile phase using a Thermo Synchronise C18 column at a UV detection wavelength of 230 nm. The method was validated for selectivity, linearity, precision, accuracy, limit of detection (LOD), limit of quantification (LOQ), solution stability, and robustness. Results: The calibration curve was linear over a concentration range of 1–20 μg/ml (r2=0.9999) with LOD and LOQ of 0.01 and 0.04 μg/ml, respectively. The intraday and interday precision and accuracy were between 0.04–1.67% and 0.04–0.78%, respectively. The results of analysis of the four brands of CMZ tablets were passed the European Pharmacopoeia specification but with a high standard deviation of mean drug content of some brands. Conclusion: This study shows that the quality of post-marketed drugs and/or the storage conditions in developing countries must be carefully assessed for a better therapeutic response.
Optical Imaging in Medicine

Optical spectroscopy is a routinely used clinical laboratory technique, and since the 1930’s has been used to examine tissue oxygenation in thin tissue sections or from surface reflection measurements. However, in the 1970’s the technique of near infrared spectroscopy (NIRS) of intact organs was first described by Frans Jobsis, a breakthrough that enabled truly non invasive measurements to be made on intact organs, allowing the technique to be applied to patients at the bedside. In the NIR (700-900 nm), oxygenation dependent changes in attenuation can be observed which arise from variations in the concentration of oxy and deoxyhaemoglobin in the blood, and of oxidised cytochrome oxidase in the cell mitochondria. Since the initial report of Jobsis, instrumental improvements now enable us to measure attenuation changes across many centimetres of tissue (most commonly brain or muscle), and techniques to quantify haemodynamic variables such as blood flow and volume have been developed.
Stabilization of the wave equation withinterior input delay and mixed Neumann-Dirichlet boundary

This paper considers the stabilization of a wave equation with interior input delay: $\mu_1u(x,t)+\mu_2u(x,t-\tau)$, where $u(x,t)$ is the control input. A new dynamic feedback control law is obtained to stabilize the closed-loop system exponentially for any time delay $\tau>0$ provided that $|\mu_1|\neq|\mu_2|$. Moreover, some sufficient conditions are given for discriminating the asymptotic stability and instability of the closed-loop system.
A Time-Series Model for Underdispersed or Overdispersed Counts

ABSTRACT It is common for time series of unbounded counts (that is, nonnegative integers) to display overdispersion relative to the Poisson. Such an overdispersed series can be modeled by a hidden Markov model with Poisson state-dependent distributions (a “Poisson–HMM”), since a Poisson–HMM allows for both overdispersion and serial dependence. Time series of underdispersed counts seems less common, but more awkward to model; a Poisson–HMM cannot cope with underdispersion. But if in a Poisson–HMM one replaces the Poisson distributions by Conway–Maxwell–Poisson distributions, one gets a class of models which can allow for under- or overdispersion (and serial dependence). In addition, this class can cope with the combination of slight overdispersion and substantial serial dependence, a combination that is apparently difficult for a Poisson–HMM to represent. We discuss the properties of this class of models, and use direct numerical maximization of likelihood to fit a range of models to three published series of counts which display underdispersion, and to a series which displays slight overdispersion plus substantial serial dependence. In addition, we illustrate how such models can be fitted without imputation when some observations are missing from the series, and how approximate standard errors of the parameter estimates can be found. Supplementary materials for this article are available online.
Automatic Optimization of One-Dimensional CNN Architecture for Fault Diagnosis of a Hydraulic Piston Pump Using Genetic Algorithm

A hydraulic piston pump is an essential component of a hydraulic transmission system and is extensively used in contemporary industrial settings. Therefore, fault diagnosis of piston pumps is a crucial topic in the engineering field. The convolutional neural network (CNN) is currently the most popular deep neural network model and has been successfully employed for fault detection and other tasks. The design and hyperparameter settings of CNNs significantly affect the overall diagnosis performance. In this study, a genetic method is proposed that can quickly investigate a specific set of potentially viable one-dimensional CNN (1D-CNN) architectures while also optimizing their hyperparameters for a fault detection task of an axial hydraulic piston pump. The proposed model is automatically designed based on a direct connect 1D-CNN block, which is another contribution of this study. The proposed method is evaluated on the raw sound signal dataset of an axial hydraulic piston pump without any signal pre-processing techniques. The experimental results demonstrate that the proposed method outperforms several well-known deep learning (DL) models in terms of fault diagnosis performance. Additionally, the suggested method uses significantly less computational power to determine the best 1D-CNN structures than most peer rivals.
Iterative space-time domain fast multiresolution sar imaging algorithms

Quadtree BackProjection (QBP) is a fast space-time domain SAR imaging algorithm that performs an iterative fractional imaging process derived from a divide and conquer strategy. Although the original derivation was based on the intuitive idea of approximating standard backprojection, the algorithm did not have an analytical justification. Furthermore, the QBP has a complicated internal structure, so the actual implementation usually has significant processing overhead. This thesis provides a mathematical analysis of the quadtree backprojection algorithm and also provides several variations of the QBP algorithm that improve its implementation. A Fourier transform analysis has been performed on the SAR data spectrum that is associated with QBP, in order to show that quadtree backprojection is equivalent to an iterative subband decomposition of the SAR data spectrum. Finally, several variations of QBP have been studied: multiresolution imaging, sensor array linearization, multiradix decompositions, and the fast QBP. Each of these has been developed to provide less complicated and more flexible implementations or to provide other imaging capabilities. Finally, the QBP algorithm has been extended to two related application areas: medical tomographic backprojection and delay-sum beamforming.
An Analytical Gate Delay Variability Model for Low-Power Applications under the Process Variations Effects

Defining the timing characteristics behavior, such as the gate delay and the oscillation period, is an essential task in integrated circuits (ICs), especially for low-power CMOS-based technologies. The nanometric-sized devices designed to achieve low-power consumption have higher threshold voltages. Hence, these devices are operated at the near-threshold regime, or slightly above the threshold. In these regions, shifts in electrical parameters (expressed in terms of drain current or threshold voltage) may severely impact the circuit behavior. Consequently, the time-dependent sources of variability (e.g., the bias temperature instability) impose a crucial reliability problem that affects time delay variability and induces slope propagation effects along the signal path. In this context, an improved analytical model to properly account for both the gate delay and its variability is presented, taking into account the properties of low-power devices. Additionally, the applicability of the model is presented in a case study of a ring oscillator. The derived equations allows a suitable estimative for the parameters’ degradation. Supported by Monte Carlo simulations, the extracted results indicate that the proposed method provides a better estimate for the ring oscillator jitter when compared to the simplified propagation of uncertainty method.