Miracle-dz/UniFAR-FTUs huggingface dataset:
Text Selection

Abstract Text data is ultra-high dimensional, which makes machine learning techniques indispensable for textual analysis. Text is often selected—journalists, speechwriters, and others craft messages to target their audiences’ limited attention. We develop an economically motivated high-dimensional selection model that improves learning from text (and from sparse counts data more generally). Our model is especially useful when the choice to include a phrase is more interesting than the choice of how frequently to repeat it. It allows for parallel estimation, making it computationally scalable. A first application revisits the partisanship of the U.S. congressional speech. We find that earlier spikes in partisanship manifested in increased repetition of different phrases, whereas the upward trend starting in the 1990s is due to distinct phrase selection. Additional applications show how our model can backcast, nowcast, and forecast macroeconomic indicators using newspaper text, and that it substantially improves out-of-sample fit relative to alternative approaches.
EFFECT OF LOSSES IN PRINTED RECTANGULAR COILS FOR COMPACT WIRELESS POWER TRANSFER SYSTEMS

Development and optimization of printed spiral coils have significant impacts on the power transfer efficiency (PTE) and operating range for magnetic resonant wireless power transfer (WPT) applications. In this paper, the effects of different material losses (substrate and conducting coating) of printed coils are considered and experimentally studied. For the purposes of comparison and finding the dominating losses, lossy loaded capacitors with equivalent series resistances have also been investigated. A four-coil system with an external capacitor-loaded (ECL) magnetic resonant WPT system is considered, and a self-resonant coil is designed and compared. Results show that the ECL resonant coil has higher PTE than the self-resonant coil with the same size and distance between the transmitting and receiving coils. Through observing the simulated results and analyzing experimental data, it can be concluded that the dominant cause of the decrease in PTE of this ECL-WPT system is the strip resistive loss of coil of 57% (0.891 dB) and the ohmic loss in ECL of 37% (0.568 dB). Meanwhile, the substrate loss significantly impacts on the PTE of the self resonant coil. The overall measured PTE is about 66% of the ECL coil at a distance of 50 mm when the above loss factors are considered. The measured results are in good agreement with the analysis and simulations.
FACTORS AFFECTING THE ADOPTION OF BIG DATA ANALYTICS IN COMPANIES

ABSTRACT With the total quantity of data doubling every two years, the low price of computing and data storage, make Big Data analytics (BDA) adoption desirable for companies, as a tool to get competitive advantage. Given the availability of free software, why have some companies failed to adopt these techniques? To answer this question, we extend the unified theory of technology adoption and use of technology model (UTAUT) adapted for the BDA context, adding two variables: resistance to use and perceived risk. We used the level of implementation of these techniques to divide companies into users and non-users of BDA. The structural models were evaluated by partial least squares (PLS). The results show the importance of good infrastructure exceeds the difficulties companies face in implementing it. While companies planning to use Big Data expect strong results, current users are more skeptical about its performance.
2 DESIGNING A STUDY TO MAXIMIZE INFORMATIONAL VALUE

• understand the importance of statistical power, boost it when needed, and consider strategies for confronting real, world chal, lenges to running highly powered studies; • consider both the benefits and drawbacks of using online samples; • distinguish between exploratory and confirmatory analyses so that you can learn as much as possible from your data; and • plan programs of research that include direct, systematic, and/or conceptual replications.
Reduction in Some Reproductive Indices of Momordica Charantia Treated Male Wistar Rats

Original Research Article The effect of Momordica charantia leaf extract was evaluated by determining blood follicle stimulating hormone (FSH), Interstitial cell stimulating hormone (ICSH) and testosterone (TET) levels as well as sperm quality and organ weight in male wistar rats, after 30 days of oral administration. The animals were randomly assigned into three (3) groups of six (6) rats each. Group one (1) served as control and received distilled water. Group two (2) and group three (3) received 200mg/kg and 400mg/kg of the hydromethanol (20%:80%) extract respectively. Results obtained showed that the extract caused no significant (P<0.05) alteration in the levels of FSH and ICSH. But there was a significant decrease in plasma TET level. There were no significant effects on testicular and epidydimal weights. There was significant impairment of sperm quality evidenced by a reduction in percentages of viable sperms, sperms with normal morphology and actively motile sperm as well as sperm count. The decrease in plasma testosterone and abnormal sperm parameters may suggest the ability of the plant extract to cause a direct toxic effect on the seminiferous tubule which may damage testosterone secreting cells thereby affecting testosterone synthesis and the production of healthy sperm. This study proved that, the leaf extract of Momordica charantia caused anti fertility effects in male wistar rats.
Adaptation to Climate Change via Adjustment in Land Leasing: Evidence from Dryland Wheat Farms

This paper investigates how dryland wheat farm operators adapt to climate through the use of land leasing in the U.S. Pacific Northwest region. Using a farm-level dataset from the U.S. Census of Agriculture, we build a statistical relationship between climate and leased acreage for dryland wheat farms. We find that a warmer and wetter climate reduces leased dryland wheat farmland, suggesting that land leasing is a potential strategy for adaptation to future climate. Using climate projections from 20 global climate models, we predict that, by 2050, leased acreage for dryland wheat farms on average will decline by 23% and 29% relative to 2012 levels under the medium and high greenhouse gas emission scenarios, respectively.
Synthesis and Characterization of Biopolymer capped Zinc ferrite nanoparticles by a thermal treatment method

Zinc ferrite(ZF) nanoparticles was synthesized by the thermal treatment method, followed by calcination from zero to 500 0 C. The ZF was stabilized using polyvinyl alcohol (PVA) to prevent agglomeration. The ZF obtained was characterized by X-ray diffraction (XRD), scanning electron microscopy (SEM) and Vibrating sample magnetometer (VSM). The XRD confirmed the good crystallinity of the sample with an average estimated crystalline size ranging from 5 to 14 nm.The SEM confirmed the morphology of the sample, with a less agglomeration for the higher concentration of the polymer and the annealed samples. The VSM confirmed the superparamagnetic nature of the sample capped with a polymer with an increase in saturation magnetization (SM) from 2.07 emu/g (un-annealed) to 6.56 emu/g (annealed). Consequently, surface encapsulation and calcination process of the ZF gave a more homogeneous size for various applications. -------------------------------------------------------------------------------------------------------------------------------------Date of Submission: 14-04-2018 Date of acceptance: 30-04-2018 -------------------------------------------------------------------------------------------------------------------------------------
A New Algorithm for Delineation of Surface Depressions and Channels

Topographic delineation is critical to watershed hydrologic modeling, which may significantly influence the accuracy of model simulations. In most traditional delineation methods, however, surface depressions are fully filled and hence, watershed-scale hydrologic modeling is based on depression-less topography. In reality, dynamic filling and spilling of depressions affect hydrologic connectivity and surface runoff processes, especially in depression-dominated areas. Thus, accounting for the internal hydrologic connectivity within a watershed is crucial to such hydrologic simulations. The objective of this study was to improve watershed delineation to further reveal such complex hydrologic connectivity. To achieve this objective, a new algorithm, HUD-DC, was developed for delineation of hydrologic units (HUs) associated with depressions and channels. Unlike the traditional delineation methods, HUD-DC considers both filled and unfilled conditions to identify depressions and their overflow thresholds, as well as all channels. Furthermore, HUs, which include puddle-based units and channel-based units, were identified based on depressions and channels and the detailed connectivity between the HUs was determined. A watershed in North Dakota was selected for testing HUD-DC, and Arc Hydro was also utilized to compare with HUD-DC in depression-oriented delineation. The results highlight the significance of depressions and the complexity of hydrologic connectivity. In addition, HUD-DC was utilized to evaluate the variations in topographic characteristics under different filling conditions, which provided helpful guidance for the identification of filling thresholds to effectively remove artifacts in digital elevation models.
Narrow-Linewidth DFB and DBR Lasers with Surface Gratings Fabricated Using UV-Nanoimprint Lithography

This thesis presents the design, modeling, and fabrication of high performance narrowlinewidth edge-emitting semiconductor distributed feedback (DFB) and distributed Bragg reflector (DBR) lasers employing surface gratings fabricated without epitaxial re-growth. The re-growth free fabrication method mitigates the risks of contamination and atmospheric oxidization in the active and waveguide layers, improving the device performance, reliability and yield. Compared to conventional buried gratings, in the surface gratings the injected carriers have much less interaction with the defect prone processed interfaces, which decreases the non-radiative recombination and the probability of degradation, increasing the reliability, particularly at high injection currents. In this work soft-stamp ultraviolet (UV)-nanoimprint lithography (NIL) has been used to define the etch masks. Unlike in conventional photolithography, the UV-NIL’s resolution is not limited by diffraction and scattering effects. Moreover, UV-NIL has low fabrication costs and high throughput, which makes it ideal for a large scale mass production. The thesis discusses how the device design can influence the emission linewidth and how this affects other laser characteristics, some of which require contradictory design parameters. For example a decreasing mirror loss reduces the linewidth but also reduces the slope efficiency, limiting the maximum output power. Also novel device design elements have been introduced to alleviate the technological limitations of the fabrication process. A laterally coupled (LC)-ridge waveguide (RWG) grating with lateral protrusions alternating on the sides of the central ridge has been employed to enable the fabrication of gratings having wider trenches than the grating period and reduced lateral current leakage. Under the technological restrictions given by the achievable etching aspect ratio, the wider trenches enable the fabrication of lower order gratings, reducing radiation losses. The fabricated devices achieved state-of-the-art characteristics: 30mW to 40mW output power with ∼10 kHz full width at half maximum (FWHM) linewidths at 300mA bias current for 780 nm DFB lasers and ∼500mW output power with <250 kHz FWHM linewidths at 1630mA bias current for 1180 nm DBR lasers. Also monolithic master oscillator power amplifier (MOPA) lasers have been fabricated to avoid the compromise between achieving a narrow linewidth and a high power as well as to enable independent control of the emission wavelength and output power. ∼7W output power was obtained for a 780 nm MOPA laser with a 3mm long DFB master oscillator (MO) section and a 4mm long tapered power amplifier (PA) section under 500mA continuous wave (CW)mode bias for the MO section and 15A pulsed-mode bias (1 μs pulse width and 1% duty cycle) for the PA section. The pulsed-mode operation of the PA section, which did not enable accurate emission linewidth measurement for the MOPA lasers, was employed because the p-side up mounting did not provide good enough thermal management.
Ultrafast and Wideband Microwave Photonic Frequency-Hopping Systems: A Review

The increasing demands to enhance information security in data transmission, providing countermeasures against jamming in military applications, as well as boosting data capacity in mobile and satellite communication, have led to a critical need for high-speed frequency-hopping systems. Conventional electronics-based frequency-hopping systems suffer from low data rate, low hopping speed, and narrow hopping-frequency bandwidth. Unfortunately, those are important aspects to facilitate frequency-hopping in emerging microwave systems. The recent advancement of microwave photonics—the use of light to process microwave signals—provides promising solutions to tackle the challenges faced by electronic frequency-hopping systems. In this paper, the challenges of achieving real-time frequency-hopping systems are examined. The operation principles and results of various microwave photonics-enabled frequency-hopping systems are comprehensively discussed, which have wide hopping-frequency bandwidth and frequency-hopping speed from nanoseconds to tens of picoseconds. Lastly, a bio-inspired jamming-avoidance system that could potentially be used for adaptive frequency-hopping is also introduced.
Process monitoring of directed-energy deposition of Inconel-718 via plume imaging

Laser-metal interactions typically results in vaporization and plume formation. These phenomena are complex and depend upon the details of the laser-vapor-melt interactions. As such, plume characteristics are sensitive to changes in process characteristics. Here, a spectroscopybased imaging technique is presented for the monitoring of directed energy deposition of Inconel 718. Plume geometry is shown to be related to the processing parameters and geometry of singlebead deposits.
Reactive extraction of propionic acid using tributyl phosphate in imidazolium-based ionic liquids: Optimization study using response surface methodology

In this work, the reactive extraction of propionic acid from aqueous solutions using imidazolium-based ionic liquids was examined. Ionic liquids, 1-butyl-3-methylimidazolium bis(trifluoromethylsulfonyl)imide ([BMIM][Tf 2 N]), and 1-butyl-3-methylimidazolium hexafluorophosphate ([BMIM][PF 6 ]) were utilized as diluents. Tributyl phosphate (TBP) as an extractant in ionic liquids was used. D-optimal design based on the response surface methodology (RSM) has been exerted to specify the effect of different variables on the reactive extraction process. Initial propionic acid concentration (2-10% w/w), extractant (TBP) concentration (0-3.00 mol.L -1 ) and temperature (25-45 ℃) were chosen as numerical variables, and type of ionic liquid was chosen as a categorical variable. Extraction efficiency, selected as a dependent variable, was calculated from the experimental data. In addition to, the model equation for the extraction efficiency was created. The optimum extraction conditions were obtained as the initial propionic acid concentration of approximately 5% (w/w), TBP concentration in ionic liquids of 3 mol.L -1 and temperature of 45 ○ C . Under these conditions, the values of extraction efficiency were determined as 85.64% for [BMIM][PF 6 ], and 81.91% for [BMIM][Tf 2 N]. This study has indicated that the systems of TBP in ionic liquids is an efficient and green reactive extraction method for the removal of propionic acid from the aqueous media .
Reinforcement-learning-based architecture for automated quantum adiabatic algorithm design

Quantum algorithm design lies in the hallmark of applications of quantum computation and simulation. Here we put forward a deep reinforcement-learning (RL) architecture for automated algorithm design in the framework of quantum-adiabatic-algorithm. Our approach is applicable to a class of problems with solution hard-to-find but easy-to-verify, e.g., searching, factorization, and NPcomplete problems. We benchmark this approach in Grover-search and 3-SAT problems, and find that the adiabatic-algorithm obtained by our RL approach leads to significant improvement in the success probability and computing speedups for both moderate and large number of qubits compared to conventional algorithms. The RL-designed algorithm is found to be qualitatively distinct from the linear-algorithm in the resultant distribution of success probability. We show that the RL approach is able to produce algorithms with improved computation-complexity scaling automatically for Grover search, and that the algorithm by this approach has emergent transferability on 3-SAT. These findings imply a huge potential for reinforcement learning application to automated quantum adiabatic algorithm design. Further considering the established complexity-equivalence of circuit and adiabatic quantum algorithms, we expect the RL-designed adiabatic algorithm to inspire novel circuit algorithms as well. Our approach is potentially applicable to different quantum hardwares from trapped-ions and optical-lattices to superconducting-qubit devices.
Subsidiary strategy and managers’ perceptions of distance to foreign markets

Purpose The purpose of this paper is to examine how headquarters’ managers perceive – cultural, administrative, geographic and economic (CAGE) – distance between countries and its influence on the strategy of international subsidiaries. Design/methodology/approach This study applies the transaction cost and behavioural theory and presents an exploratory and qualitative methodology approach through six semi-structured in-depth interviews to evaluate managers’ perceptions of distance between countries. Findings The research findings show that cultural and economic distances indeed have a major influence on subsidiary strategy and a smaller impact of administrative and geographic dimensions, which results into forced changes on the marketing-mix, i.e. product, price, design and brand, as well as on the level of autonomy granted to foreign subsidiaries. Research limitations/implications The limitation is related to the home country and the entry mode of foreign direct investment. The findings presented here reflect the nature and behaviour of Portuguese companies with subsidiaries. Practical implications The research provides recommendations for managers to be aware of the influence of more than one dimension of distance between countries to improve their decision-making of standardisation-adaptation strategy for foreign subsidiaries. Furthermore, the study stresses that managers’ perceptions may lead to the conclusion that proximity and knowledge of foreign markets does not make international business easier. Originality/value This empirical research not only tests the transaction cost theory and behavioural theory on managers’ decisions to invest abroad but also promotes organisational changes to achieve the suitable strategy for international subsidiaries. The study contributes to the area of international business by positing six research propositions concerning distance between countries to be tested in future studies.
University of Groningen Movement Control Strategies in a Dynamic Balance Task in Children With and Without Developmental Coordination Disorder Jelsma,

Our study aimed to analyze movement control strategies using predefined criteria for amplitude and differences in these strategies between children with and without DCD. Children with (n1⁄4 28) and without DCD (n1⁄4 15) were included. A video-observation-tool was used to score the moving body parts during a Wii Fit slalom task over multiple time points. Two-step cluster analysis was used to extract distinct movement strategies. Two different movement strategies were identified that were independently validated by a measure of task performance and a subjective mark of quality of the movement. Initial differences between groups and changes over time toward the more successful strategy were found in both groups, albeit in a different percentage. This study shows that the more efficient movement strategy is seen in the majority of the TD children and only in a small number of children with DCD, even after practice.
Assessing Global Environmental Sustainability Via an Unsupervised Clustering Framework

The importance of sustainable development has risen in recent years due to the significant number of people affected by lack of access to essential resources as well as the need to prepare for and adapt to intensifying climate change and rapid urbanization. Modeling frameworks capable of effectively assessing and tracking sustainability lie at the heart of creating effective policies to address these issues. Conventional frameworks, such as the Environmental Performance Index (EPI), that support such policies often involve ranking countries based on a weighted sum of a number of relevant environmental metrics. However, the selection and weighing processes are often biased. Moreover, the ranking process fails to provide policymakers with possible avenues to improve their country’s environmental sustainability. This study aimed to address these gaps by proposing a novel data-driven framework to assess the environmental sustainability of countries objectively by leveraging unsupervised learning theory. Specifically, this framework harnesses a clustering technique known as Self-Organized Maps to group countries based on their characteristic environmental performance metrics and track progression in terms of shifts within clusters over time. The results support the hypothesis that the inconsistencies in the EPI calculation can lead to misrepresentations of the relative sustainability of countries over time. The proposed framework, which does not rely on ranking or data transformations, enables countries to make more informed decisions by identifying effective and specific pathways towards improving their environmental sustainability.
High‐order cubature rules for tetrahedra

In this paper, we construct new high‐order numerical integration schemes for tetrahedra, with positive weights and integration points that are in the interior of the domain. The construction of cubature rules is a challenging problem, which requires the solution of strongly nonlinear algebraic (moment) equations with side conditions given by affine inequality constraints. We present a robust algorithm based on a sequence of three modified Newton procedures to solve the constrained minimization problem. In the literature, numerical integration rules for the tetrahedron are available up to order p=15. We obtain integration rules for the tetrahedron from p=2 to p=20, which are computed using multiprecision arithmetic. For p≤15, our approach provides integration rules that have the same or fewer number of integration points than existing rules; for p=16 to p=20, our rules are new. Numerical tests are presented that verify the polynomial‐precision of the cubature rules. Convergence studies are performed for the integration of exponential, rational, weakly singular and trigonometric test functions over tetrahedra with flat and curved faces. In all tests, improvements in accuracy is realized as p is increased, though in some cases nonmonotonic convergence is observed.