Miracle-dz/UniFAR-FTUs huggingface dataset:
Chemistry and deposition in the Model of Atmospheric composition at Global and Regional scales using Inversion Techniques for Trace gas Emissions (MAGRITTE v1.1) – Part 1: Chemical mechanism

Abstract. A new chemical mechanism for the oxidation of biogenic volatile organic compounds (BVOCs) is presented and implemented in the Model of Atmospheric composition at Global and Regional scales using Inversion Techniques for Trace gas Emissions (MAGRITTE v1.1). With a total of 105 organic species and over 265 gas-phase reactions, 69 photodissociations, and 7 heterogeneous reactions, the mechanism treats the chemical degradation of isoprene – its main focus – as well as acetaldehyde, acetone, methylbutenol, and the family of monoterpenes. Regarding isoprene, the mechanism incorporates a state-of-the-art representation of its oxidation scheme accounting for all major advances put forward in recent theoretical and laboratory studies. The recycling of OH radicals in isoprene oxidation through the isomerization of Z-δ-hydroxyperoxy radicals is found to enhance OH concentrations by up to 40 % over western Amazonia in the boundary layer and by 10 %–15 % over the southeastern US and Siberia in July. The model and its chemical mechanism are evaluated against the suite of chemical measurements from the SEAC4RS (Studies of Emissions and Atmospheric Composition, Clouds and Climate Coupling by Regional Surveys) airborne campaign, demonstrating a good overall agreement for major isoprene oxidation products, although the aerosol hydrolysis of tertiary and non-tertiary nitrates remain poorly constrained. The comparisons for methylnitrate indicate a very low nitrate yield (<3×10-4) in the CH3O2+NO reaction. The oxidation of isoprene, acetone, and acetaldehyde by OH is shown to be a substantial source of enols and keto-enols, primarily through the photolysis of multifunctional carbonyls generated in their oxidation schemes. Oxidation of those enols by OH radicals constitutes a sizable source of carboxylic acids estimated at 9 Tg (HC(O)OH) yr−1 and 11 Tg(CH3C(O)OH) yr−1 or ∼20 % of their global identified source. The ozonolysis of alkenes is found to be a smaller source of HC(O)OH (6 Tg HC(O)OH yr−1) than previously estimated, due to several factors including the strong deposition sink of hydroxymethyl hydroperoxide (HMHP).
Immunohistochemistry

This unit describes several methods for localizing specific antigens in various tissue and cell preparations using immunohistochemistry (IHC). Protocols describe preparation of suitable material for IHC including fresh, unfixed, frozen tissue specimens; unfixed cells, either freshly isolated or derived from suspension or adherent cultures; or fixed, paraffin‐embedded tissue sections. By careful selection of reagents, it is possible to detect two or even three antigens simultaneously. For antigens that are sensitive to fixative, it may be necessary to unmask the antigen by the antigen‐retrieval technique. If there is cross‐reactivity between the secondary antibody and antigens present in the target cells or tissue, the secondary antibody can be preabsorbed. Several new, sensitive amplification techniques are currently available. The different IHC protocols are represented schematically and summarized in a table that also lists advantages and disadvantages of each approach. Causes of background staining and ways to eliminate it are also discussed. Curr. Protoc. Immunol. 103:21.4. 1‐21.4. 26. ©2013 by John Wiley & Sons, Inc.
Non-congestion packet loss detection for TCP error recovery using wireless links

Most commonly used data transfer protocols assume that every packet loss is an indication of network congestion. This interaction between the error recovery and the congestion control procedures results in a low utilisation of the link when there is an appreciable rate of losses due to link errors. This issue is significant for wireless links, particularly those with a long propagation delay. A solution for this problem of inability to separate congestion packet loss from other types of packet loss has been presented and analysed using simulation techniques.
On the electron boundary conditions in full PIC simulations of plasma thruster plumes

The collisionless, steady state expansion into vacuum of a warm electron, cold ion plasma thruster plume is studied with a set of new electrostatic particle-in-cell model and globally-consistent boundary conditions that discriminate between reﬂected and escaping electrons. As a proof of concept, several simulations are analyzed. Results from both two-dimensional planar and axisymmetric plasma plumes are discussed. In particular, the electrons’ anisothermal and anisotropic behavior in the plume is recovered.
Regional new particle formation as modulators of cloud condensation nuclei and cloud droplet number in the eastern Mediterranean

Abstract. A significant fraction of atmospheric particles that serve as cloud condensation nuclei (CCN) are thought to originate from the condensational growth of new particle formation (NPF) from the gas phase. Here, 7 years of continuous aerosol and meteorological measurements (June 2008 to May 2015) at a remote background site of the eastern Mediterranean were recorded and analyzed to assess the impact of NPF (of 162 episodes identified) on CCN and cloud droplet number concentration (CDNC) formation in the region. A new metric is introduced to quantitatively determine the initiation and duration of the influence of NPF on the CCN spectrum. NPF days were found to increase CCN concentrations (from 0.10 % to 1.00 % supersaturation) between 29 % and 77 %. Enhanced CCN concentrations from NPF are mostly observed, as expected, under low preexisting particle concentrations and occur in the afternoon, relatively later in the winter and autumn than in the summer. Potential impacts of NPF on cloud formation were quantified by introducing the observed aerosol size distributions and chemical composition into an established cloud droplet parameterization. We find that the supersaturations that develop are very low (ranging between 0.03 % and 0.27 %) for typical boundary layer dynamics (σw ∼0.3 m s−1) and NPF is found to enhance CDNC by a modest 13 %. This considerable contrast between CCN and CDNC response is in part from the different supersaturation levels considered, but also because supersaturation drops from increasing CCN because of water vapor competition effects during the process of droplet formation. The low cloud supersaturation further delays the appearance of NPF impacts on CDNC to clouds formed in the late evening and nighttime – which has important implications for the extent and types of indirect effects induced by NPF events. An analysis based on CCN concentrations using prescribed supersaturation can provide very different, even misleading, conclusions and should therefore be avoided. The proposed approach here offers a simple, yet highly effective way for a more realistic impact assessment of NPF events on cloud formation.
Application of a generalized probabilistic descent method to dynamic time warping-based speech recognition

Although several kinds of discriminative training methods based on artificial neural networks have been vigorously tested, the pursuit of highly capable classification of variable-duration speech patterns has been unsatisfactory. In this light, the authors evaluate a generalized probabilistic descent method (GPD) in designing a speech recognizer incorporated with the dynamic time warping methodology. The algorithm can be viewed as generalized learning vector quantization suited to the dynamic programming-based time warping. Experiments were conducted on two tasks: English syllable classification and Japanese phoneme classification. Results clearly demonstrate that GPD can be a viable candidate for a method to realize a high-performance speech recognizer. <<ETX>>
High-performance crystal oscillator circuits: theory and application

A general theory that allows the accurate linear and nonlinear analysis of any crystal oscillator circuit is presented. It is based on the high Q of the resonator and on a very few nonlimiting assumptions. The special case of the three-point oscillator, that includes Peirce and one-pin circuits, is analyzed in more detail. A clear insight into the linear behavior, including the effect of losses, is obtained by means of the circular locus of the circuit impedance. A basic condition for oscillation and simple analytic expressions are derived in the lossless case for frequency pulling, critical transconductance, and start-up time constant. The effects of nonlinearities on amplitude and on frequency stability are analyzed. As an application, a 2-MHz CMOS oscillator which uses amplitude stabilization to minimize power consumption and to eliminate the effects of nonlinearities on frequency is described. The chip, implemented in a 3- mu m p-well low-voltage process, includes a three-stage frequency divider and consumes 0.9 mu A at 1.5 V. The measured frequency stability is 0.05 p.p.m. /V in the range 1.1-5 V of supply voltage. Temperature effect on the circuit itself is less than 0.1 p.p.m. from -10 to +60 degrees C. >
Effect of temperature on the formation of highly oxygenated organic molecules (HOMs) from alpha-pinene ozonolysis

Abstract. Highly oxygenated organic molecules (HOMs) are important contributors to secondary organic aerosol (SOA) and new-particle formation (NPF) in the boreal atmosphere. This newly discovered class of molecules is efficiently formed from atmospheric oxidation of biogenic volatile organic compounds (VOCs), such as monoterpenes, through a process called autoxidation. This process, in which peroxy-radical intermediates isomerize to allow addition of molecular oxygen, is expected to be highly temperature-dependent. Here, we studied the dynamics of HOM formation during α-pinene ozonolysis experiments performed at three different temperatures, 20, 0 and −15 ∘C, in the Aarhus University Research on Aerosol (AURA) chamber. We found that the HOM formation, under our experimental conditions (50 ppb α-pinene and 100 ppb ozone), decreased considerably at lower temperature, with molar yields dropping by around a factor of 50 when experiments were performed at 0 ∘C, compared to 20 ∘C. At −15 ∘C, the HOM signals were already close to the detection limit of the nitrate-based chemical ionization atmospheric pressure interface time-of-flight (CI-APi-TOF) mass spectrometer used for measuring gas-phase HOMs. Surprisingly, comparing spectra measured at 0 and 20 ∘C, ratios between HOMs of different oxidation levels, e.g., the typical HOM products C10H14O7, C10H14O9, and C10H14O11, changed considerably less than the total HOM yields. More oxidized species have undergone more isomerization steps; yet, at lower temperature, they did not decrease more than the less oxidized species. One possible explanation is that the primary rate-limiting steps forming these HOMs occur before the products become oxygenated enough to be detected by our CI-APi-TOF (i.e., typically seven or more oxygen atoms). The strong temperature dependence of HOM formation was observed under temperatures highly relevant to the boreal forest, but the exact magnitude of this effect in the atmosphere will be much more complex: the fate of peroxy radicals is a competition between autoxidation (influenced by temperature and VOC type) and bimolecular termination pathways (influenced mainly by concentration of reaction partners). While the temperature influence is likely smaller in the boreal atmosphere than in our chamber, both the magnitude and complexity of this effect clearly deserve more consideration in future studies in order to estimate the ultimate role of HOMs on SOA and NPF under different atmospheric conditions.
Scattering functions of carved-ellipsoid-shaped particles

Motivated by the enriched topologies from the newly discovered nano-scaled molecular clusters, custom carved-ellipsoid models are built and their scattering functions are explored. The scattering functions of these models are derived in ellipsoidal coordinates. The theoretical scattering curves of these models can be further obtained through numerical calculation. These models have been successfully applied to the fitting of experimental scattering curves of some so-called wheel-shaped metal oxide molecular clusters.
Controle de enchentes no lote por poço de infiltração de água pluvial sob nova concepção

RESUMO O objetivo deste trabalho foi avaliar uma nova concepção de poço de infiltração como técnica de controle de drenagem pluvial na fonte. Esse poço, denominado P-GHidro, possui furos na parede dos anéis de concreto, camada de brita externa aos anéis para melhorar a distribuição de água, pré-filtro de geotêxtil na tampa e filtros adicionais no fundo e na lateral, entre a brita e o solo. Usou-se como referência o poço de infiltração comumente empregado em São Carlos, São Paulo (P-SC), cuja construção foi realizada com anéis de concreto justapostos ao solo sem furos laterais e sem pré-filtro. Foram realizados seis ensaios de chuvas simuladas para cada poço de infiltração. Os dados experimentais de vazão de água infiltrada foram modelados pelo método de Puls. A condutividade hidráulica, constante ou variada, foi empregada como parâmetro de calibração do modelo aos dados experimentais; o ajuste foi avaliado por meio dos coeficientes de determinação (R2) e de Nash-Sutcliffe (NS). O P-GHidro apresentou melhor desempenho na infiltração de água pluvial, com volume armazenado 25% menor e tempos de esvaziamento 4% menores que os do P-SC. A modelagem apresentou boa representatividade dos dados experimentais para condutividade hidráulica constante (média de R2 de 0,92 e de NS de 0,56) e melhor ainda para condutividade hidráulica variada (média de R2 de 0,97 e de NS de 0,97).
A new method to determine the aerosol optical properties from multiple-wavelength O4 absorptions by MAX-DOAS observation

Abstract. Ground-based multi-axis differential optical absorption spectroscopy (MAX-DOAS) observation was carried out from November 2016 to February 2017 in Beijing, China, to measure the O4 absorptions in UV and visible bands and further to illustrate its relationship with aerosol optical properties (AOPs) under different weather types. According to relative humidity, visibility, and PM2.5, we classified the observation periods into clear, light-haze, haze, heavy-haze, fog, and rainy weather conditions. There are obvious differences for measured AOPs under different weather conditions, especially scattering coefficient (σsca) and absorption coefficient (σsca). It was also found that both the O4 differential slant column densities (DSCDs) at the UV and visible bands varied in the order of clear days > light-haze days > haze days > heavy-haze days > fog days. The correlation coefficients (R2) between O4 DSCDs at 360.8 and 477.1 nm mainly varied in the order of clear days > light-haze days > haze days > heavy-haze days. Based on the statistics of O4 DSCDs at an elevation angle 1∘ with the corresponding linear regression between UV and visible bands of segmental periods, the relationships between O4 DSCDs and AOPs were established. It should mainly be clear or light-haze days when the correlation slope is greater than 1.0, with a correlation coefficient (R2) greater than 0.9, and O4 DSCDs mainly greater than 2.5×1043 molec. cm−2. Meanwhile, σsca and σabs are less than 45 and 12 Mm−1, respectively. For haze or heavy-haze days, the correlation slope is less than 0.6, with an R2 less than 0.8, and O4 DSCDs mainly less than 1.3×1043 molec. cm−2, under which σsca and σabs are mainly located at 200–900 and 20–60 Mm−1. Additionally, the determination method was well validated based on another MAX-DOAS measurement at Gucheng from 19 to 27 November 2016. For more precise and accurate inversion of AOPs, more detailed look-up tables for O4 multiple-wavelength absorptions need to be developed. Since the ground surface AOPs were determined using MAX-DOAS observation at a 1∘ elevation in this study, we hope to highlight the potential of retrieved vertical spatially resolved AOPs being expected when multiple elevation angles of MAX-DOAS observation are used together.
Security audit trail analysis using inductively generated predictive rules

A time-based inductive learning approach to security audit trail analysis is presented. The approach uses a time-based inductive engine to generate rule-based sequential patterns that characterize the behavior of a user. The time-based inductive approach substantially increases the discriminating capability of an anomaly detection system due to the added dimension of information given in the sequential relationships between security events. It is shown that the use of rule-based sequential patterns allows a security auditing system to capture characteristics of user behavior that may be otherwise intractable using traditional statistical approaches. The approach also may help security management to focus on a few potentially hostile security events inside an entire user log-in session. <<ETX>>
Hybrid PD and adaptive backstepping control for self-balancing two-wheel electric scooter

This paper proposes a combination of adaptive self-balancing controller and the left and right turning PD controller for self-balancing two-wheel electric scooter (eScooter). An adaptive selfbalancing controller is synthesized by the backstepping approach and the Lyapunov stability theory. The proposed adaptive controller allows the design of a feedback control that stabilizes self-balancing control of eScooter in the presence of uncertainty and perturbation. Additionally, the sensor signals are treated by Kalman filters and the CAN networks are applied to communication among modules of eScooter. Simulation and experiment results are shown to analyze and validate the performance of proposed controller.
Automatic generation of behaviors for mobile robot by GA with automatically generated action rule-base

To design behaviors of a mobile robot for realizing given tasks, a designer has to make a set of rules which generate a proper action from a state of sensors. In general, however, it is difficult that the designer makes all set of rules since the number of rules is very large and the proper action for a state of sensors is not clear. Many methods have been proposed to solve such a problem using reinforcement learning genetic programming or genetic algorithm and so on. However, those methods are not sufficiently applied to the case in which the environment changes or is unknown. In this paper, new method which is efficiently applied to such a difficult case is proposed. The proposed method is constructed by genetic algorithm and action rule-base. The experimental results, using a mobile robot simulator, shows that the mobile robot can properly act in the unknown environments.
Study on the Use of SNS(Social Network Service) for Tasks:Focus on the Task-Media Fit

As SNS has increased its influence on the society as a whole, companies also have started to consider how to take advantage of the new service paying specific attention to its characteristics of immediacy, sharability and interactivity. This study aims to circumstantiate the relationship between a task support tool of SNS and task-media fit, user characteristics and performance by focusing on its usage in work field. To address this issue, a Task-Technology Fit model is used to propose a research model considering the characteristics of SNS as a social element, information technology as well as its user characteristics. The outcome shows that job characteristics, virtual competence and media characteristics have a significant influence on task-media fit, whereas virtual competence and SNS characteristics variables have a significant influence on SNS usage. Besides, task-media fit has a significant influence on SNS usage and work performance while SNS usage has a significant influence on work performance. The study suggests that strategic use of SNS helps improve work performance and these individual characteristics should be considered in planning of SNS utilizing strategy.
Overcoming Barriers to Successful Delivery of Distance-Learning Courses

Abstract For this study, the authors collected data from 81 business professors who taught distance-learning courses at 61 U.S. business schools accredited by the American Assembly of Collegiate Schools of Business (AACSB). Findings indicate that the professors (a) primarily used self-training for the design and delivery of on-line courses, (b) believed that the technology was not sufficiently reliable, (c) believed that the greatest benefit of distance learning was flexibility for students, and (d) perceived a student-centered teaching approach as necessary for successful distance-education courses.
Photochemistry on the bottom side of the mesospheric Na layer

Abstract. Lidar observations of the mesospheric Na layer have revealed considerable diurnal variations, particularly on the bottom side of the layer, where more than an order-of-magnitude increase in Na density has been observed below 80 km after sunrise. In this paper, multi-year Na lidar observations are utilized over a full diurnal cycle at Utah State University (USU) (41.8∘ N, 111.8∘ W) and a global atmospheric model of Na with 0.5 km vertical resolution in the mesosphere and lower thermosphere (WACCM-Na) to explore the dramatic changes of Na density on the bottom side of the layer. Photolysis of the principal reservoir NaHCO3 is shown to be primarily responsible for the increase in Na after sunrise, amplified by the increased rate of reaction of NaHCO3 with atomic H, which is mainly produced from the photolysis of H2O and the reaction of OH with O3. This finding is further supported by Na lidar observation at USU during the solar eclipse (>96 % totality) event on 21 August 2017, when a decrease and recovery of the Na density on the bottom side of the layer were observed. Lastly, the model simulation shows that the Fe density below around 80 km increases more strongly and earlier than observed Na changes during sunrise because of the considerably faster photolysis rate of its major reservoir of FeOH.
Research on Real-Time Network Forensics Based on Improved Data Mining Algorithm

According to the characteristics of high precision and massive amounts of data processing during real-time network forensic, combining the defects of traditional Apriori algorithm which scan data sets more times, the paper improved Apriori algorithm, the data set is divided into parallel processing blocks, and then use dynamic itemsets counting method weight each block to construct tree, and depth-first search the tree, mark the data set which is divided out of the data block, and dynamic evaluation all the items set which has counted in order to acquire frequent itemsets, reducing the number of scanning, improved data processing capability of network forensics, use K-mediods algorithm for secondary mining to improve the accuracy, reduce network data loss, improve legal effect of network crime evidence.