Miracle-dz/UniFAR-FTUs huggingface dataset:
Design Techniques for High-Efficiency Envelope-Tracking Supply Modulator for 5th Generation Communication

This brief provides a brief tutorial on designing a high efficiency envelope-tracking supply modulator with recent techniques. Design challenges for 5G communication applications are given. Detailed techniques covering topology derivation, multi-level and fast-speed switching converter design considerations, voltage step-up and –down function implementations, linear amplifier bandwidth improvements and measurement setup are discussed, providing design guidelines and considerations.
On the Vibrations of a Rigid Solid Hung by Kinematic Chains

In this paper we consider two situations. In the first, all kinematic chains are elastic, while the second situation is characterized by one rigid kinematic chain, with the rest of them being elastic. In addition, the kinematic joints are considered to be rigid. The calculations are performed using the screw coordinates. For the free vibrations of the rigid solid we determined the rigidity matrix and the eigenpulsations in both cases. It was proved that the results in the second case cannot be considered as limits for the results of the first situation, putting infinite values for the elements of the rigidity matrix of one kinematic chain. We also developed the theory for the forced vibrations of the system. A numerical application is considered and a great variety of cases are developed and discussed. The results obtained for the forced vibrations are presented and discussed. The paper combines elastic and rigid kinematic chains, as well as general configurations of the kinematic chains. The method presented here may be used for any number of kinematic chains, no matter if the structure is symmetrical or asymmetrical.
INFLUENCE OF RISK MANAGEMENT IN BUILDING PROJECTS IN KENYA: A CASE OF BUILDING PROJECTS IN WESTLANDS SUB - COUNTY

v TABLE OF CONTENT . vi LIST OF TABLES . xi LIST OF FIGURES . xii ABBREVIATIONSAND ACRONYMS . xiii CHAPTER ONE: INTRODUCTION . 1 1.1 Background Information of the study . 1 1.2 Statement of the Problem . 4 1.3 Purpose of the Study . 5 1.4 Objectives of the study . 5 1.5 Research Questions . 6 1.6 Significance of the Study . 6 1.6. 1 Project Actors . 6 1.6. 2 Practitioners . 6 1.6. 3 Policy Makers . 7 vii 1.7 Delimitation of the Study . 7 1.8 Limitations of the Study . 7 1.9 Basic assumptions of the study . 8 1.10 Definition of Significant Terms as used in the Study . 8 1.11 Organization of the study . 9 CHAPTER TWO:LITERATURE REVIEW . 10 2.
An automatic systolic peak detector of blood pressure waveforms using 4th order cumulants

Abstract The arterial blood pressure (ABP) holds a lot of information about the cardiovascular system. To analyse the ABP signal, at first the pulse wave has to be detected correctly. Due to influences, e.g. of noise, an accurate beat detection is a challenging task. In this work, a novel real-time ABP detector based on higher-order statistics is presented. The method uses the 4th order cumulants for ABP-peak detection. To evaluate this detector, the Fantasia database freely available at physionet was used. In this database, 142,936 systolic peaks were available to check the efficiency of the beat detector. A sensitivity of 99.91% and a positive predictive value of 99.50% were achieved with the novel method.
Recent progress in ultra-low formaldehyde emitting adhesive systems and formaldehyde scavengers in wood-based panels: a review

ABSTRACT Traditional wood-based panels are produced with synthetic, formaldehyde-based adhesives, commonly made from fossil-derived constituents, such as urea, phenol, melamine, etc. Along with their numerous advantages, such as chemical versatility, high reactivity and excellent adhesive performance, these adhesives are characterized by certain problems, connected with the hazardous volatile organic compounds (VOCs), mostly free formaldehyde in the adhesives and the formaldehyde emission from the finished wood composites, which is carcinogenic to humans and harmful to the environment. The growing environmental concerns and stringent legislative requirements to the formaldehyde emission from wood-based panels have posed new challenges to researchers and industrial practice, related to the development of sustainable, eco-friendly wood-based panels with close-to-zero formaldehyde emission. The most common methods to reduce the formaldehyde emission from wood-based panels have been to decrease the free formaldehyde in the adhesive by modifying the adhesive (like lowering the molar ratio of formaldehyde to urea in UF resin) or by using formaldehyde scavengers, one group of scavengers being for adhesives by mixing or reacting and the second one scavengers for wood-based panels as post-treatments. Another way is to use alternative bio-based adhesives, however, there are still substantial challenges for the complete replacement of formaldehyde-based adhesives with bio-based adhesives, mainly because of their relatively low bonding strength, poor water resistance, etc. This article presents a review and analysis of the current state of research in the field of low formaldehyde emission wood adhesives and formaldehyde scavengers for manufacturing low-toxic, eco-friendly wood composites.
Finding similar questions in large-scale community QA forums

Question answering forums are rapidly growing in size with no automated ability to refer to and reuse existing answers. In this paper, we develop a methodology for finding semantically related questions. The task is difficult since 1) key pieces of information are often buried in extraneous details in the question body and 2) available annotations are scarce and fragmented, driven largely by participants. We design a novel combination of recurrent and convolutional models (gated convolutions) to effectively map questions to their semantic representations. The models are pre-trained within an encoder-decoder framework (from body to title) on the basis of the entire raw corpus, and fine-tuned discriminatively from limited annotations. Our evaluation demonstrates that our model yields a 10% gain over a standard IR baseline, and a 6% gain over standard neural network architectures (including CNNs and LSTMs) trained analogously. 1 Thesis Supervisor: Regina Barzilay Title: Professor 'Code and data are available at https://github. com/taolei87/rcnn
Treatment of Diabetic Macular Edema with Aflibercept and Micropulse Laser (DAM Study)

Purpose To investigate the safety and efficacy of micropulse (MP) macular laser in combination with intravitreal aflibercept for the treatment of center-involved diabetic macular edema (CI-DME). Methods A single-blind prospective randomized controlled pilot trial was performed. In total, 30 eyes of 30 patients with CI-DME and best corrected visual acuity (BCVA) between, and including, 20/30 and 20/400 were enrolled. Enrolled eyes were randomized to 2 groups. Group 1 received intravitreal aflibercept injections (IVT-AFL) with sham laser. Group 2 received IVT-AFL with MP laser. Both groups were followed every 4 weeks for 48 weeks and retreatment was performed on pro re nata basis according to preset criteria. The main outcome measure was the average number of intravitreal injections for each group at 48 weeks. Secondary outcome measures included changes in BCVA and central macular thickness (CMT) at 24 and 48 weeks. Results The average number of intravitreal injections at 48 weeks was similar between the groups (8.5±3.3 in Group 1 vs 7.9±3.6 in Group 2, p=0.61). After 48 weeks, both groups demonstrated an improvement in BCVA and CMT. However, the difference in improvement between the groups was not statistically significant (p=0.18 for BCVA and p=0.57 for CMT). Conclusion Intravitreal injections of aflibercept led to improvements in BCVA and CMT at 24 and 48 weeks. Addition of MP laser to eyes in group 2 did not offer additional benefit in reducing treatment burden or improving CMT. Eyes that received MP laser showed a numerically greater improvement in BCVA, although this was not statistically significant. Clinicaltrials.gov Identifier NCT03143192 March 8, 2017.
Solving the Single-Row Facility Layout Problem by K-Medoids Memetic Permutation Group

The single-row facility layout problem (SRFLP) is concerned with arranging facilities along a straight line so as to minimize the sum of the products of the flow costs and distances among all facility pairs. SRFLP has rich practical applications and is however NP-hard. In this article, we first investigate a dedicated symmetry-breaking approach based on the permutation group theory for reducing the solution space of SRFLP. Relevant symmetry properties are identified through the alternating group of the original solution space or the corresponding coordinate rotation space. Then, a memetic algorithm is proposed to explore promising search regions regarding the reduced solution space. The memetic algorithm employs a problem-specific crossover operator guided by ${k}$ -medoids clustering technique to produce meaningful offspring solutions. The algorithm additionally uses a simulated annealing procedure to intensively exploit a given search region and a distance-and-quality-based population management strategy to ensure a reasonable diversity of the population. Experimental results on commonly used benchmark instances and newly introduced large-scale instances with sizes up to 2000 facilities show that the proposed algorithm competes favorably with state-of-the-art SRFLP algorithms. It attains all but one previous best known upper bounds (BKS) and discovers new upper bounds for 33 instances out of the 93 popular benchmark instances.
Growth and characterization of uniformly distributed triangular single-crystalline hexagonal boron nitride grains on liquid copper surface

Single-layer hexagonal boron nitride (h-BN) is a two-dimensional (2D) material with a wide band gap and extraordinary mechanical, thermal and optical properties. It has promising applications in optoelectronics, electronics and photovoltaics. Low-pressure (150 Pa) chemical vapor deposition (LPCVD) was used to prepare uniformly distributed single-crystalline triangular h-BN grains and continuous film on liquid copper surface. A series of microscopic and spectroscopic methods were performed to characterize the morphology, crystalline structure and quality, component and thickness. It was found that h-BN grains turned into circles at higher background pressure (1000 Pa), which was due to the change in the growth mechanism from equilibrium controlled to deposition controlled. Small islands formed on primary h-BN grains because of higher concentration of precursor product. Compared to the higher background pressure, the synthetic h-BN films at low background pressure exhibited larger domain size, lower nucleation density, and no adlayer growth. Due to randomly distributed polar h-BN grains, the grain boundaries formed along the h-BN domains after merging. Typical patterns formed via the coalescence of triangular h-BN grains indicating the merging mode of growth, including edge-to-edge and edge-to-point modes. This work provides a pathway for the preparation of uniformly distributed single-crystalline h-BN grains and an in-depth understanding of the growth and merging process on liquid Cu surface.
Trends in intraseasonal temperature variability in Europe, 1961–2018

While long‐term changes in measures of central tendency of climate elements, that is, mean temperature, are well acknowledged, studies of trends in measures of their variability are much less common. This is despite the fact that trends in variability can have higher effect on climate extremes than trends in mean. Here, four measures of intraseasonal variability are examined: (a) standard deviation of mean daily temperature, (b) the range between the 90th and 10th quantile of mean daily temperature, (c) mean absolute value of day‐to‐day temperature change, and (d) one‐day lagged temporal autocorrelation. ECA&D daily data from 168 stations and linear regression method are utilized to calculate trends of these characteristics in period from 1961 to 2018. Significant trends (positive and negative) are revealed with substantial differences between seasons, regions and measures. The most considerable decreases in temperature variability were recorded in winter, for temporal autocorrelation in eastern Europe and for variance‐based measures in northern Europe. For example, the standard deviation has decreased by more than 10% in the Arctic Ocean. This can indicate a decrease in the frequency of cold extremes in Scandinavia. On the contrary, increasing persistence may suggest a greater likelihood of cold extremes in the East European Plain. Increases in variability prevail only in summer, but not for all measures and not as clearly as decreases in winter. Trends in temporal autocorrelation and day‐to‐day change appear to be sensitive to data issues, such as inhomogeneities and changes in observational procedures.
Development of nanoparticles for pharmaceutical preparations using supercritical techniques

Abstract This review focuses on nanoparticle (NP) synthesis and particle size design using supercritical fluid (SCF) technology for pharmaceutical formulations. SCF technology is seen as a pioneering step forward in particle size design, and also plays a critical role in addressing the problem of residual solvents in pharmaceutical and biomedical research. In SCF technology, one of the most important components is environmentally friendly supercritical CO2 (scCO2) fluid, which is very common and cost-effective because nontoxic green technology is used for the formation of nanomedicine in drug delivery. In the case of pharmaceutical science, numerous complex procedures are required in order to manufacture NPs. The working principles of the rapid expansion of supercritical solutions (RESS), supercritical antisolvent (SAS), supercritical fluid extraction of emulsions (SFEE), solution-enhanced dispersion by supercritical fluids (SEDS), rapid expansion of supercritical solution into a liquid solvent (RESOLV), and particles from gas-saturated solution (PGSS) are widely used throughout the industry. Most of the supercritical (SC) approaches (total 23 methods) including the newly established methods are cited in this manuscript. This study offers a detailed overview of fundamental principles and relevant roles, advantages, and difficulties in the creation of SCF methods for the formation of NPs. It gives the clear concept to select the proper method, solvent, active ingredients, and polymers in NP preparation.
Estimation of Electromagnetic Properties for 2D Inhomogeneous Media Using Neural Networks

Electromagnetic measurements are widely used to gain information about an object through interaction of electromagnetic fields with the physical properties of this object. The inversion problem is the process of estimating object parameters from electromagnetic records. This problem has a nonlinear nature and can be formulated as an optimization scheme. In this paper, we introduce an inversion methodology to estimate the electrical properties of a two-dimensional inhomogeneous layered scattering object. The proposed methodology deals with the inversion problem as a learning process through two multilayer perceptron artificial neural network designs. Several neural network design parameters were tuned to achieve the best inversion performance. Moreover, the proposed neural networks were tested against noise presence in terms of error criteria and proved to be effective in solving the inverse scattering problem.
Recent Advances and Applications of Rapid Microbial Assessment from a Food Safety Perspective

Unsafe food is estimated to cause 600 million cases of foodborne disease, annually. Thus, the development of methods that could assist in the prevention of foodborne diseases is of high interest. This review summarizes the recent progress toward rapid microbial assessment through (i) spectroscopic techniques, (ii) spectral imaging techniques, (iii) biosensors and (iv) sensors designed to mimic human senses. These methods often produce complex and high-dimensional data that cannot be analyzed with conventional statistical methods. Multivariate statistics and machine learning approaches seemed to be valuable for these methods so as to “translate” measurements to microbial estimations. However, a great proportion of the models reported in the literature misuse these approaches, which may lead to models with low predictive power under generic conditions. Overall, all the methods showed great potential for rapid microbial assessment. Biosensors are closer to wide-scale implementation followed by spectroscopic techniques and then by spectral imaging techniques and sensors designed to mimic human senses.
Improving the estimation of ship emissions using the high‐spatiotemporal resolution wind fields simulated by the Weather Research and Forecast model: A case study in China

Ships, sailing in favorable wind or obstructed by wind, will operate with different output power of the engines, and the exhaust emissions will be different even though the ships are sailing at the same ground speed. In this study, the influence of wind was taken into consideration; the ship emission inventory (0.025° × 0.025°) in China of a full year (2014) was reassessed. A speed modification model was employed to figure out the actual output speed of ships by integrating AIS data and the hourly wind. The Weather Research and Forecast (WRF) model was applied to predict the hourly real‐time wind field. The spatial and temporal changes in emissions between the results calculated by the proposed method and our previous study were presented. Overall, when considering the influence of wind, the total ship emissions for the year would increase. In this study, the total estimated emissions of SO2, NOx, PM10, PM2.5, HC, and CO in the area were 1.286 × 106, 2.583 × 106, 2.135× 105, 1.967 × 105, 1.522 × 105, and 3.053 × 105 t(metric tons) in 2014, respectively. Under the influence of wind, the proportion of the regions’ emissions to the total was close to that of the previous study. For SO2 and NOx, emissions presented significant monthly variations. On a monthly timescale, the difference in emissions was more obvious between the results considering and not considering the wind, relative to that on a yearly basis. This study adjusted the method of ship emission estimation, which modified the ship emission inventory over an hourly timescale.
Multimodal Analysis of “Energen” Ads

This paper discusses the multimodal analysis of Energen advertising. Print media advertisements and electronic media advertisements are texts that have a complex meaning. The complexity of meaning occurs because to convey messages in advertisements, not only language elements are used but also nonverbal language elements and other visual means. Therefore, to understand the complexity of meaning, it is necessary to do a multimodal analysis in the advertisement. The multimodal analysis discussed in this paper uses the theory of functional systemic linguistics (LSF). The multimodal analysis model was developed from a combination of multimodal theory (Anstey & Bull, 2010), and multimodal analysis by Kress and Van Leeuwen (1996-2006). From the analysis of Energen's advertisements, it is found that Energen's advertisements have a multimodal semiotic system which includes linguistic, visual, audio, gestural, and spatial elements. Keywords: multimodal, advertising
Modelling Energy Transition in Germany: An Analysis through Ordinary Differential Equations and System Dynamics

This paper proposes the application of a multivariate diffusion model, based on ordinary differential equations, to investigate the energy transition in Germany. Specifically, the model is able to analyze the dynamic interdependencies between coal, gas and renewables in the energy market. A system dynamics representation of the model is also performed, allowing a deeper understanding of the system and the set-up of suitable strategic interventions through a simulation exercise. Such simulation provides a useful indication of how renewable energy consumption may be stimulated as a result of well-specified policies.
Adaptive State Space Models with Applications to the Business Cycle and Financial Stress

In this paper we develop a new framework for the analysis of state space models with time-varying parameters. We let the driver of the time variation be the score of the predictive likelihood and derive a new filter that allows us to estimate simultaneously the state vector and the time-varying parameters. In this setup the model remains Gaussian, the likelihood function can be evaluated using the Kalman filter and the model parameters can be estimated via maximum likelihood, without requiring the use of computationally intensive methods. Using a Monte Carlo exercise we show that the proposed method works well for a number of different data generating processes. We also present two empirical applications. In the former we improve the measurement of GDP growth by combining alternative noisy measures, in the latter we construct an index of financial stress and evaluate its usefulness in nowcasting GDP growth in real time. Given that a variety of time series models have a state space representation, the proposed methodology is of wide interest in econometrics and applied macroeconomics.
Towards the Full Experience of Playing Drums on a Virtual Drum Kit

A key concept of drums kits is the ability to customize elements and their placement. It is part of the creative process which influences the playing style. We discuss elements of drum kits customization, existing haptic interactive systems for drums, and technologies which would make it possible to implement a virtual drum set which provides the full experience of playing drums.
SLEEPNOISE - A SIMULATOR BASED STUDY OF THE EFFECTS OF NOISE ON DRIVER SLEEPINESS

In the current study, a detailed model of in-vehicle road noise was developed in order to test effects of road noise on driver sleepiness. The model synthesizes realistic road noise based on real world measurements of road texture and of corresponding interior noise. Two different scenarios were used, representing a mid-sized hatchback car on a coarse road texture versus a large wagon on a smooth road. The synthesized noise was validated against in-vehicle recordings, and was ultimately used to investigate influence on driver sleepiness. Results show that the model is well suited for such studies, and that there was indeed an effect on driver sleepiness. In addition, a carry-over effect was found for the onset of the noise test cases. It suggests that the effect on e.g. self-reported sleepiness was determined by the first stimulus presented, masking the effect of later stimuli, thus emphasizing the need for methodological design considerations.