Miracle-dz/UniFAR-FTUs huggingface dataset:
Electromagnetic Interference Mitigation for Inverter fed AC Drives

Problem statement: In switched mode PWM inverter EMI noise occurs during high (dv/dt) transient period. This EMI noise is mitigated using Active Common mode EMI filter in front of the source. Approach: This study proposes a new active common mode Electromagnetic Interference (EMI) filter for switched mode PWM Inverter applications. The proposed filter is based on current sensing and compensation circuit which utilizes fas t transistor amplifier for current compensation. The amplifier is biased with an isolated low voltag e DC power supply. Hence it is possible to construct an active filter independent of the sourc e voltage of equipment. Thus this filter can be used in any application regardless of working volta ge. The proposed switched mode PWM inverter operated in 180° mode of operation. It's o therwise called as quasi square wave mode. Results: Simulation of output wave form is verified by usin g MATLAB Simulink model results and also its effectiveness has been verified hardwa re output wave forms. The hardware for this project is designed and developed for 50V, 50Hz thr ee phase Fractional Horse Power (FHP) motor. Conclusion: In this Study the concept of the new active common mode EMI filter and quasi square PWM inverter has been proposed. The corresponding simulated output waveforms are verified with the Active Common mode EMI filter; it is possi ble to use low-voltage transistors for the amplifie r by introducing coupling capacitors between the power line and the amplifier circuit. Thus the ACEF can be applied to various power electronic systems regardless of the working voltage. Also it helps in improving the performance of additional filter stag es.
Boundary layer aerosol chemistry during TexAQS/GoMACCS 2006: Insights into aerosol sources and transformation processes

[1] The air quality and climate forcing impacts of atmospheric aerosols in a metropolitan region depend on the amount, composition, and size of the aerosol transported into the region; the input and removal of aerosols and aerosol precursors within the region; and the subsequent chemical processing in the atmosphere. These factors were studied in the Houston-Galveston-Gulf of Mexico region, aboard the NOAA R/V Ronald H. Brown during the Texas Air Quality Study and Gulf of Mexico Atmospheric Composition and Climate Study (TexAQS/GoMACCS 2006). The aerosol measured in the Gulf of Mexico during onshore flow (low radon concentrations indicating no contact with land for several days) was highly impacted by Saharan dust and what appear to be ship emissions (acidic sulfate and nitrate). Mean (median) mass concentrations of the total submicrometer and supermicrometer aerosol were 6.5 (4.6) μg m−3 and 17.2 (8.7) μg m−3, respectively. These mass loadings of “background” aerosol are much higher than typically observed in the marine atmosphere and thus have a substantial impact on the radiative energy balance over the Gulf of Mexico and particulate matter (PM) loadings (air quality) in the Houston-Galveston area. As this background aerosol moved onshore, local urban and industrial sources added an organic rich submicrometer component (66% particulate organic matter (POM), 20% sulfate, 14% elemental carbon) but no significant supermicrometer aerosol. The resulting aerosol had mean (median) mass concentrations of the total submicrometer and supermicrometer aerosol of 10.0 (9.1) μg m−3 and 16.8 (11.2) μg m−3, respectively. These air masses, with minimal processing of urban emissions contained the highest SO2/(SO2 + SO4=) ratios and the highest hydrocarbon-like organic aerosol to total organic aerosol ratios (HOA/POM). In contrast, during periods of offshore flow, the aerosol was more processed and, therefore, much richer in oxygenated organic aerosol (OOA). Mean (median) mass concentrations of the total submicrometer and supermicrometer aerosol were 20.8 (18.6) μg m−3 and 7.4 (5.0) μg m−3, respectively. Sorting air masses based on their trajectories and time over land provides a means to examine the effects of transport and subsequent chemical processing. Understanding and parameterizing these processes is critical for the chemical transport modeling that forms the basis for air quality forecasts and radiative forcing calculations.
Cathodoluminescence of Powder Layers of Nanometer-Sized Y2O3:Eu and Micrometer-Sized ZnO:Zn Phosphor Particles

Copyright @ The Electrochemical Society, Inc. 2013. All rights reserved. Except as provided under U.S. copyright law, this work may not be reproduced, resold, distributed, or modified without the express permission of The Electrochemical Society (ECS). The archival version of this work was published in The ECS Journal of Solid State Science and Technology, 2(9), R201 - R207, 2013.
A New Instrument to Measure the Mass of Nano-Particles from Internal Combustion Engines

Particles from internal combustion engines are known to reduce visibility, harm human health, and affect climate. A new instrument called the Couette centrifugal particle mass analyzer (Couette CPMA) has been developed to measure the mass of nano-particles. A unique system of forces allows for particle mass measurements over a wide range with high resolution. The Couette CPMA was used to measure the effective density, fractal dimension, and mass concentration of particles emitted from a light-duty diesel vehicle.
Pressure-induced magnetism in rotated graphene bilayers

Using ab initio methods based on the density functional theory we show that rotated graphene bilayers at angles different from the magic ones can have an electronic spectrum similar to those by applying moderate external pressures. We find that for an angle of $5.08^{\circ}$ and a pressure of 2.19 GPa the spin restricted spectrum displays a flat band at the Fermi level similar to the one found at magic angles. In addition, the spin unrestricted calculations show a correlated ferromagnetic ground state with a total magnetic moment of 3.7 $\mu_{B}$ per unit cell being mostly localized in the AA stacking region of the Moir\'{e} pattern. The possibility of antiferromagnetic order is considered but not calculated. Doping the system destroys the magnetic moments. The plausibility of BCS superconductivity in the doped system is analyzed.
Visual object tracking based on random compression of multi-channel haar-like feature

The compressed sensing algorithm has achieved good application e ect in the eld of visual tracking. In this paper, a moving object tracking algorithm based on the random compression of multi-channel Haar-like features is proposed. Firstly, a new multi-channel Haar-like feature is introduced by considered the color distribution of the object, and extract it by random compression projection. Then, the characteristics of the feature distribution in the samples are studied, and a weighted naive Bayesian classi er is constructed. Finally, in order to adapt to the change of the object appearance, the classi er parameters are updated in real time. The e ectiveness of the algorithm is veri ed by contrast experiments which carried on the open and challenging video sequences.
Sucrose intensity coding and decision-making in rat gustatory cortices

Sucrose’s sweet intensity is one attribute contributing to the overconsumption of high-energy palatable foods. However, it is not known how sucrose intensity is encoded and used to make perceptual decisions by neurons in taste-sensitive cortices. We trained rats in a sucrose intensity discrimination task and found that sucrose evoked a widespread response in neurons recorded in posterior-Insula (pIC), anterior-Insula (aIC), and Orbitofrontal cortex (OFC). Remarkably, only a few Intensity-selective neurons conveyed the most information about sucrose’s intensity, indicating that for sweetness the gustatory system used a compact and distributed code. Sucrose intensity was encoded in both firing-rates and spike-timing. The pIC, aIC, and OFC neurons tracked movement direction, with OFC neurons yielding the most robust response. aIC and OFC neurons encoded the subject’s choices, whereas all three regions tracked reward omission. Overall, these multimodal areas provide a neural representation of perceived sucrose intensity, and of task-related information underlying perceptual decision-making.
Towards a femtosecond laser micro-machined optofluidic device for distinguishing algae species

We demonstrate a small device with a microfluidic channel and an integrated waveguide as a compact rudimentary tool for the detection, real-time monitoring, and potentially classification of algae. In order to reduce parasitic noise the micro-device used a curved subsurface optical waveguide to illuminate particles transiting through a microfluidic channel. The changes in the transmitted signal are monitored using a quadrant-cell photo-detector. The signals wavelets from the different quadrants are used to qualitatively distinguish different families of algae. Additional information, such as flow direction, is also provided. The channel and waveguide are fabricated out of a monolithic fused-silica substrate using a femtosecond laser-writing process combined with chemical etching. This proof-of-concept device paves the way for more elaborate femtosecond laser-based optofluidic micro-instruments incorporating waveguide network designed for the real-time analysis of cells and microorganisms in the field.
Using Inhabitation in Bounded Combinatory Logic with Intersection Types for GUI Synthesis

We describe ongoing work on a framework for automatic composition synthesis from a repository of software components which is based on combinatory logic with intersection types. The idea is that components are modelled as typed combinators, and an algorithm for inhabitation — is there a combinatory term e with type τ relative to an environment Γ? — can be used to synthesize compositions. Here, Γ represents the repository in the form of typed combinators, τ specifies the synthesis goal, and e is the synthesized program. We illustrate our approach by an application to synthesis from GUI-components.
The evolving landscape of learning technology

This paper provides an overview of the current and emerging issues in learning technology research, concentrating on structural issues such as infrastructure, policy and organizational context. It updates the vision of technology outlined by Squires' (1999) concept of peripatetic electronic teachers (PETs) where Information and Communication Technologies (ICT) provide an enabling medium to allow teachers to act as freelance agents in a virtual world and reflects to what extent this vision has been realized The paper begins with a survey of some of the key areas of ICT development and provides a contextualizing framework for the area in terms of external agendas and policy drivers. It then focuses upon learning technology developments which have occurred in the last five years in the UK and offers a number of alternative taxonomies to describe this. The paper concludes with a discussion of the issues which arise from this work. DOI:10.1080/0968776020100302
DEVELOPMENT OF A BLOOD TESTING DEVICE BASED ON LOCALIZED SURFACE PLASMON RESONANCE

We developed a novel blood testing device which extracts plasma from a minute amount of whole blood and detects specific proteins in the plasma using LSPR (localized surface plasmon resonance). We detected an antigen-antibody reaction by measuring light scattering by gold nanoparticles in the device, and demonstrated that the present device permits detection of tPA (tissue plasminogen activator). I. INTRODUCTION The concern for healthcare and preventive medical care is rising with increase of the lifestyle-related diseases and population aging. There is going to be a greater demand for periodical and on-site diagnosable blood tests which are carried out at home by nonprofessional people. Then, many research groups have already reported about microfluidic devices to separate blood for simple blood testing. For example, the microfluidic devices which extract blood plasma using the Zweifach-Fung effect were developed(1). However, these devices require flow control using a pump. Also, the microfluidic device which separates blood into cells and plasma by dielectrophoresis was developed(2). However, this device causes hemolysis and blood deterioration due to joule heat. Therefore, we developed a microfluidic device for plasma extraction using capillary force without external driving sources. Moreover, we developed a novel technique for LSPR-based non-labeling detection of biomolecules in the device.
Mechanics of pegmatite intrusion

The position, shape, orientation, and to some extent the size of pegmatite bodies are controlled by a complex interplay among pegmatite fluid pressures, rheologic state of the host rocks, lithostatic and directed stresses, pore-water pressures, strength and ductility anisotropies, and dilational directions. Pressures of pegmatite fluids must overcome confining nonnal stresses and, where applicable, tensile strengths at intrusive sites before intrusion takes place. In the upper crust, where brittle conditions prevail, lithostatic and directed-stress conditions combine with strength anisotropies-such as fractures, cleavage, schistosity, or bedding-to produce various preferred directions of minimum resistance to intrusion. Pegmatites encountering these conditions are tabular and have a preferred orientation normal to these directions. At lower levels in the crust, ductile hydrostatic conditions promote the intrusion of lensoid to irregular pegmatites. Changes in shapes and attitudes of pegmatites in the Winnipeg River and Yellowknife districts of Canada, in the Black Hills and Colorado of the United States, in Greenland and in Afghanistan all can be interpreted in terms of the theoretical models developed for the different combinations ofthese factors.
Spatial variability and temporal dynamics of surface water pCO 2 , D O 2 / Ar and dimethylsulfide in the Ross Sea , Antarctica

We report results from two surveys of pCO2, biological O2 saturation (DO2/Ar) and dimethylsulfide (DMS) in surface waters of the Ross Sea polynya. Measurements were made during early spring (November 2006–December 2006) and mid-summer (December 2005–January 2006) using ship-board membrane inlet mass spectrometry (MIMS) for high spatial resolution (i.e. sub-km) analysis. During the early spring survey, the polynya was in the initial stages of development and exhibited a rapid increase in open water area and phytoplankton biomass over the course of our 3 week occupation. We observed a rapid transition from a net heterotrophic ice-covered system (supersaturated pCO2 and undersaturated O2) to a high productivity regime associated with a Phaeocystis-dominated phytoplankton bloom. The timing of the early spring phytoplankton bloom was closely tied to increasing sea surface temperature across the polynya, as well as reduced wind speeds and ice cover, leading to enhanced vertical stratification. There was a strong correlation between pCO2, DO2/Ar, DMS and chlorophyll a (Chl a) during the spring phytoplankton bloom, indicating a strong biological imprint on gas distributions. Box model calculations suggest that pCO2 drawdown was largely attributable to net community production, while gas exchange and shoaling mixed layers also exerted a strong control on the re-equilibration of mixed layer O2 with the overlying atmosphere. DMS concentrations were closely coupled to Phaeocystis biomass across the early spring polynya, with maximum concentrations
A PERFORMANCE MODEL FOR CORE SYSTEM MONITORING FUNCTIONS

System monitoring platforms offer advanced functionality to help IT organizations manage their resources and understand system behavior. These platforms collect, act on, and visualize data about running systems. The performance of a monitoring system under a given workload must be understood in advance in order to achieve identified performance objectives. Myriad system monitoring platforms exist for implementation by organizations, each offering distinguishing features. Most exhibit a similar system architecture consisting of a central monitoring server, a monitoring datastore, and hosts and services to monitor. Scheduling, obtaining and persisting the status of monitored hosts and services forms the primary workload placed on the monitoring system. This paper presents a closed queuing network (QN) model that predicts response time and utilization for this primary workload placed on a monitoring system. The model accounts for monitoring frequency, CPU and disk consumption at the monitoring server, and response time of the monitored system. Experiments conducted with the open source Nagios monitoring platform validate the model predictions across several workloads.
Model-Based Variable Decorrelation in Linear Regression

Linear regression outcomes (estimates, prevision) are known to be damaged by highly correlated covariates. However most modern datasets are expected to mechanically convey more and more highly correlated covariates due to the global increase of the amount of variables they contain. We propose to explicitly model such correlations by a family of linear regressions between the covariates. The structure of correlations is found with an mcmc algorithm aiming at optimizing a specific bic criterion. This hierarchical-like approach leads to a joint probability distribution on both the initial response variable and the linearly explained covariates. Then, marginalisation on the linearly explained covariates produces a parsimonious correlation-free regression model from which classical procedures for estimating regression coefficient, including any variable selection procedures, can be plugged. Both simulated and real-life datasets from steel industry, where correlated variables are frequent, highlight that this proposed covariates pretreatment-like method has two essential benefits: First, it offers a real readability of the linear links between covariates; Second, it improves significantly efficiency of classical estimation/selection methods which are performed after. An r package (CorReg), available on the cran, implements this new method.
External Return to Education in Poland

In the article social rate of return to education is considered. As is pointed out in various research papers social return rate exceeds the pure technical rate of return by considerable margin. However, it is hard to calculate adequate figure due to methodological and data problems. The model used in the article is based on a comparative advantage theory. It contains two equations: one for technical and social rate of return to education, second deals with non-random selection for different education regimes. We find that private rate of return is over 7% yearly and therefore is still among the highest in Europe and there exists additional 1.5% social return to higher education.
TREE INDUCTION : A COMPARISON OF TWO FAMILIES

Decision tree (DT) induction is among the more popular of the data mining techniques. An important component of DT induction algorithms is the splitting method, with the most commonly used method being based on the conditional entropy family. However, it is well known that there is no single splitting method that will give the best performance for all problem instances. In this paper we explore the relative performance Conditional Entropy family and another family that is based on the Class-Attribute Mutual Information (CAMI) measure. Our results suggest that while some datasets are insensitive to the choice of splitting methods, other datasets are very sensitive to the choice of splitting methods. For example, some of the CAMI family methods may be more appropriate than GainRatio (GR) for datasets where all non-class attributes are nominal; some of the CAMI methods perform as well as GR for datasets where all the non-class attributes are either integer or continuous. Given the fact that it is never known beforehand which splitting method will lead to the best DT for the given dataset, and given the relatively good performance of the CAMI methods, it seems appropriate to suggest that splitting methods from the CAMI family should be included in data mining toolsets.
The Role of Metacognitive Processes in the Regulation of Memory Performance

The increased interest in consciousness during the past two decades has opened once again the long-standing issue regarding the causal role of conscious experience in behavior. Is consciousness an inherent component of cognitive functioning, or is it merely an epiphenomenon that—from an information-processing standpoint—could just as well be done without. Among students of metacognition there is an implicit assumption that the subjective experience associated with monitoring one's own cognitive processing does in fact guide and regulate action. Thus, for instance, if we believe that we will not remember the name of a person who has just been introduced to us (a low judgment of learning), we may take special measures to commit the name to memory. When we fail to recall that name in a subsequent encounter with the person, we will probably spend more time searching for it if we have a strong gut feeling that we should know the name (a strong feeling of knowing). And if the name "George" finally does come to mind, we will still hesitate to burst out with "Hello George" if we are not quite sure that that really is his name (a low confidence judgment). In this chapter, we focus on the last stage of the process of remembering and examine the conditions that make one act on a retrieved piece of information. In particular, we address the question of how the metamemory