bluuebunny/crossref_metadata_2025_split huggingface dataset:
Chlorine oxidation of VOCs at a semi-rural site in Beijing: significant chlorine liberation from ClNO2 and subsequent gas- and particle-phase Cl–VOC production
Authors: Le Breton Michael , Hallquist Åsa M. , Pathak Ravi Kant , Simpson David , Wang Yujue , Johansson John , Zheng Jing , Yang Yudong , Shang Dongjie , Wang Haichao , Liu Qianyun , Chan Chak , Wang Tao , Bannan Thomas J. , Priestley Michael , Percival Carl J. , Shallcross Dudley E. , Lu Keding , Guo Song , Hu Min , Hallquist Mattias 
Published: September 2018

Abstract. Nitryl chloride (ClNO2) accumulation at night acts as a significant reservoir for active chlorine and impacts the following day's photochemistry when the chlorine atom is liberated at sunrise. Here, we report simultaneous measurements of N2O5 and a suite of inorganic halogens including ClNO2 and reactions of chloride with volatile organic compounds (Cl–VOCs) in the gas and particle phases utilising the Filter Inlet for Gas and AEROsols time-of-flight chemical ionisation mass spectrometer (FIGAERO-ToF-CIMS) during an intensive measurement campaign 40 km northwest of Beijing in May and June 2016. A maximum mixing ratio of 2900 ppt of ClNO2 was observed with a mean campaign nighttime mixing ratio of 487 ppt, appearing to have an anthropogenic source supported by correlation with SO2, CO and benzene, which often persisted at high levels after sunrise until midday. This was attributed to such high mixing ratios persisting after numerous e-folding times of the photolytic lifetime enabling the chlorine atom production to reach 2.3  ×  105 molecules cm−3 from ClNO2 alone, peaking at 09:30 LT and up to 8.4  ×  105 molecules cm−3 when including the supporting inorganic halogen measurements.Cl–VOCs were observed in the particle and gas phases for the first time at high time resolution and illustrate how the iodide ToF-CIMS can detect unique markers of chlorine atom chemistry in ambient air from both biogenic and anthropogenic sources. Their presence and abundance can be explained via time series of their measured and steady-state calculated precursors, enabling the assessment of competing OH and chlorine atom oxidation via measurements of products from both of these mechanisms and their relative contribution to secondary organic aerosol (SOA) formation.
Springtime aerosol load as observed from ground-based and airborne lidars over northern Norway
Authors: Chazette Patrick , Raut Jean-Christophe , Totems Julien 
Published: September 2018

Abstract. To investigate the origin of springtime aerosols in the Arctic region we
performed ground-based and airborne 355 nm Raman lidar observations in the
north of Norway (Hammerfest). Two lidars were embedded (i) on an ultralight
aircraft for vertical (nadir) or horizontal line-of-sight measurements and
(ii) in an air-conditioned van on the ground for vertical (zenith)
measurements. This field experiment was designed as part of the Pollution in
the ARCtic System (PARCS) project of the French Arctic Initiative and took
place from 13 to 26 May 2016. The consistency among lidar measurements is
verified by comparing nadir, horizontal line of sight, and ground-based Raman
lidar profiles. Dispersion of the order of 0.01 km−1 is obtained among
lidar-derived aerosol extinction coefficients at 355 nm. The aerosol load
measured in the first 3 km of the troposphere remains low throughout the
campaign, with aerosol optical thickness (AOT) of 0.1 at 355 nm (∼0.05
at 550 nm). The main contributors to the evolution of the aerosol load at
low altitude prove to be one of the flares of the nearby Melkøya gas
processing facility, the oceanic source, and the transport of aerosols from
industrial sites in Russia. Moreover, ground-based lidar measurements allowed
us to identify three cases of long-range aerosol transport (between 3 and
8 km above the mean sea level). Using back trajectories computed with the
Lagrangian model FLEXPART-WRF, these aerosol plumes are shown to be the
result of the strong forest fires that occurred in the area of Fort McMurray,
in Canada. They can at most double the AOT value over the Arctic area, with
an anomaly of 0.1 on the AOT at 355 nm.
Quantitative analysis of suture lines in Carboniferous ammonoids
Authors: Wegerer Michael , De Baets Kenneth , Korn Dieter 
Published: September 2018

Abstract. Two morphometric
methods are applied and compared for the analysis of suture lines in Early
Carboniferous ammonoids of the superfamilies Pericycloidea, Girtyoceratoidea
and Goniatitoidea. We analysed (1) classic metric data (proportions of the
width and depths or heights of lobes and saddles) using multivariate
statistic methods and (2) outline data of the external lobe and the
ventrolateral saddle of the same ammonoid taxa using the elliptic Fourier
analysis. Both methods lead to similar results and simultaneously demonstrate
ontogenetic and phylogenetic trends of these ammonoids. Our results are
consistent with three previously suggested evolutionary patterns: (1) a
general decrease of the amplitude of lobes and saddles, (2) a proportional
widening of the external lobe and (3) a heightening of the median saddle.
Including effects of watershed heterogeneity in the curve number method using variable initial abstraction
Authors: Santikari Vijay P. , Murdoch Lawrence C. 
Published: September 2018

Abstract. The curve number (CN) method was developed more than half a century ago and is still used in many watershed and water-quality models to estimate direct runoff from a rainfall event. Despite its popularity, the method is plagued by a conceptual problem where CN is assumed to be constant for a given set of watershed conditions, but many field observations show that CN decreases with event rainfall (P). Recent studies indicate that heterogeneity within the watershed is the cause of this behavior, but the governing mechanism remains poorly understood. This study shows that heterogeneity in initial abstraction, Ia, can be used to explain how CN varies with P. By conventional definition, Ia is equal to the cumulative rainfall before the onset of runoff and is assumed to be constant for a given set of watershed conditions. Our analysis shows that the total storage in Ia (IaT) is constant, but the effective Ia varies with P, and is equal to the filled portion ofIaT, which we call IaF. CN calculated using IaF varies with P similar to published field observations. This motivated modifications to the CN method, called variable Ia models (VIMs), which replace Ia with IaF. VIMs were evaluated against conventional models CM0.2 (λ  =  0.2) and CMλ (calibrated λ) in their ability to predict runoff data generated using a distributed parameter CN model. The performance of CM0.2 was the poorest, whereas those of the VIMs were the best in predicting overall runoff and watershed heterogeneity. VIMs also predicted the runoff from smaller events better than the CMs and eliminated the false prediction of zero-runoffs, which is a common shortcoming of the CMs. We conclude that including variable Ia accounts for heterogeneity and improves the performance of the CN method while retaining its simplicity.
English Language and Literature Students’ Perceptions of Critical Thinking
Authors: Tosuncuoglu Irfan 
Published: September 2018

The fundamental purpose of the function of thinking is to attribute meaning to events in our lives, classify these events into categories and identify them subjectively. As an important dimension of education on thinking, the teaching of critical thinking since the 1950s has attained a wide conceptual framework. Accepted as a factor that facilitates the aquisition and comprehension of information, critical thinking is a desirable learning outcome of education. Some of the characteristics and properties of critical thinking are being aware, systematic, flexible and patient, encompassing open-meaning, metacognition, reconstruction, motivation and discussion. From this point, the perceptions of the students of Karabuk University, English Language and Literature Department, regarding critical thinking, were investigated in detail, in the Spring semester of the academic year 2017-2018. This study is a descriptive one and utilises the survey model to determine the levels of critical thinking in 222 teacher candidates, comprised of students ranging from freshmen to seniors and from both daytime and evening education. The findings have been evaluated and a set of conclusions have been drawn. While a statistical difference according to classes was not found when Anova results were analysed on the sub-dimensions of metacognition, flexibility, systematicity, open-mindedness, a difference was found between the sophomore and senior students on the sub-dimension of perseverance-patience.
Diagnosis of Infectious Diseases in the Lower Respiratory Tract: A Cytopathologist's Perspective
Authors: Baldassarri Rebecca J. , Kumar Deepika , Baldassarri Stephen , Cai Guoping 
Published: September 2018

Context.—Respiratory cytology continues to play an important role in the diagnosis of lower respiratory tract infections. Prompt, accurate diagnosis of causative organisms is of paramount importance, particularly in immunosuppressed patients. In addition, a rapidly expanding arsenal of ancillary testing is now available, aiding tremendously in organism identification.Objective.—To provide an updated review on the cytomorphologic features of common organisms in lower respiratory tract infection. Relevant ancillary tests, differential diagnoses, and potential pitfalls of organism identification will also be discussed.Data Sources.—Data for this review were gathered from PubMed searches of infectious diseases of the lower respiratory tract, especially related to the diagnoses.Conclusions.—The lower respiratory tract is subject to infection by a wide variety of infectious agents. Pathologists should be familiar with common organisms, including their general clinical characteristics, cytomorphologic features, differential diagnoses, and ancillary methods of detection. Above all, correlation with microbiologic and clinical information is necessary to make a confident diagnosis of infection.
Nonparabolic effects in multiple quantum well structures and influence of external magnetic field on dipole matrix elements
Authors: Demić Aleksandar , Radovanović Jelena , Milanović Vitomir 
Published: September 2018

We present a method of modeling of nonparabolic effects (NPE) in quantum nanostructures by using second order perturbation theory. We apply this model on multiple quantum well structures and consider the influence of external magneticfield on dipole matrix element which is usually considered constant. The dipole matrix element directly influences the optical gain, and our model can provide a better insight to how NPE and magnetic field influence the gain of quantum nanostructures.
Joint Effect of Heterogeneous Intrinsic Noise Sources on Instability of MEMS Resonators
Authors: Jakšić Olga , Jokić Ivana , Frantlović Miloš , Randjelović Danijela , Tanasković Dragan , Lazić Žarko , Vasiljević-Radović Dana 
Published: September 2018

This article's focus is on the numerical estimation of the overall instability of microelectromechanical-system-based (MEMS) resonators, caused by intrinsic noise mechanisms that are different in nature (electrical, mechanical or chemical). Heterogeneous intrinsic noise sources in MEMS resonators that have been addressed here are Johnson–Nyquist noise, 1/f noise, noise caused by temperature fluctuations and adsorptiondesorption induced noise. Their models are given first (based on analytical modeling or based on empirical expressions with experimentally obtained parameters). Then it is shown how each one contributes to the phase noise, a unique figure of merit of resonators instability. Material dependent constants  and knee position in noise spectrum, needed for empirical formulae referring to 1/f noise, have been obtained experimentally, by measurements of noise of MEMS components produced in the Centre of Microelectronic Technologies of the Institute of Chemistry, Technology and Metallurgy in Belgrade. According to these measurements,  varies in the range from 0.776.10-4 to 2.26.10-4 and cut off frequency for 1/f noise varies from 147 Hz to 1 kHz. The determined values are then used for the modeling of micro-resonator phase noise with electrical origin and overall phase noise of a micro-resonator. Numerical example for calculation of overall phase noise is given for a micro-cantilever, produced by the same technology as measured components. The outlined noise analysis can be easily extended and applied to noise analysis of MEMS resonator of an arbitrary shape.
Preventive Thermographic Diagnostic of a HV Busbar Disconnector
Authors: Šaraba Predrag , Ljuboje Zoran , Popović Božidar , Krsmanović Dražan 
Published: September 2018

For the purpose of increasing quality, continuity and, at the same time, of increasing reliability and decreasing the losses in an electric power system (EPS), there is an emerging need for preventive diagnostic testing. From the standpoint of an electric power system availability, it is desirable to perform as many tests as possible without a violation of operating conditions of the system itself. The paper presents the thermographic testing of a HV disconnector, as an online testing with the aim of preventive maintenance and condition diagnosis of particular elements, as well as the suggestions for taking adequate measures with the aim of removing potential malfunctions. For the testing results to be quality and to give a reliable information, the load of a facility must be bigger that 50% of the nominal power. On the basis of obtained thermograms, the analysis of the disconnector and its contacts is performed, as well as of the contacts towards other elements in the facility.
An Improved Design of Gallager Mapping for LDPC-coded BICM-ID System
Authors: Zhou Lin , Huang Weicheng , Peng Shengliang , Chen Yan , He Yucheng 
Published: September 2018

Gallager mapping uses different signal points with different probabilities by assigning several labels for one signal point, and thus provides a promising approach to achieving shaping gains. An important issue in Gallager mapping is how to assign labels for signal points. In this paper, two optimized design rules for Gallager mapping of bit-interleaved coded modulation scheme with iterative decoding (BICM-ID) are proposed, where the Hamming distance among the labels for one signal point should be minimized. The extrinsic information transfer (EXIT) technique is utilized to design and analyze the proposed mapping patterns. Compared with conventional Gallager mapping, our proposed method provides extra shaping gain for the LDPC-coded BICM-ID system. And our proposed method supplies better performance than conventional uniform mapping with the same spectrum efficiency.
LUT Based Generalized Parallel Counters for State - of - art FPGAs
Authors: Khurshid Burhan 
Published: September 2018

Generalized Parallel Counters (GPCs) are frequently used in constructing high speed compressor trees. Previous work has focused on achieving efficient mapping of GPCs on FPGAs by using a combination of general Look-up table (LUT) fabric and specialized fast carry chains. The resulting structures are purely combinational and cannot be efficiently pipelined to achieve the potential FPGA performance. In this paper, we take an alternate approach and try to eliminate the fast carry chain from the GPC structure. We present a heuristic that maps GPCs on FPGAS using only general LUT fabric. The resultant GPCs are then easily re-timed by placing registers at the fan-out nodes of each LUT. We have used our heuristic on various GPCs reported in prior work. Our heuristic successfully eliminates the carry chain from the GPC structure with the same LUT count in most of the cases. Experimental results using Xilinx Kintex-7 FPGAs show a considerable reduction in critical path and dynamic power dissipation with same area utilization in most of the cases.
Recognition Method of Drinking-driving Behaviors Based on PCA and RBF Neural Network
Authors: Sun Yifan , Zhang Jinglei , Wang Xiaoyuan , Wang Zhangu , Yu Jie 
Published: September 2018

Drinking-driving behaviors are important causes of road traffic injuries, which are serious threats to the lives and property of traffic participants. Therefore, reducing the occurrences of drinking-driving behaviors has become an important problem of traffic safety research. Forty-eight male drivers and six female drivers who could drink moderate alcohol were chosen as participants. The drivers’ physiological data, operation behavior data, car running data, and driving environment data were collected by designing various virtual traffic scenes and organizing drivers to conduct driving simulation experiments. The original variables were analyzed by the Principal Component Analysis (PCA), and seven principal components were extracted as the input vector of the Radial Basis Function (RBF) neural network. The principal component data was used to train and verify the RBF neural network. The Levenberg-Marquardt (LM) algorithm was chosen to train the parameters of the neural network and build a drinking-driving recognition model based on PCA and RBF neural network to realize an accurate recognition of drinking-driving behaviors. The test results showed that the drinking-driving recognition model based on PCA and RBF neural network could identify drinking drivers accurately during driving process with a recognition accuracy of 92.01%, and the operation efficiency of the model was high. The research can provide useful reference for prevention and treatment of drinking and driving and traffic safety maintenance.
Creating Infrastructure for Urban Mobility: Case Study of Skopje
Authors: Koltovska Nečoska Daniela , Ivanjko Edouard , Pavleski Daniel 
Published: September 2018

In this paper, a methodology for creating and testing new proposed transport infrastructure is presented. It is based on microscopic traffic simulation of current and forecasted traffic demand and in-depth analysis of traffic flow. The most congested boulevard in Skopje has been chosen as a use case. Real-world traffic flow data was collected and used in the calibration and validation of a microscopic simulation model. Three possible configurations of new urban mobility infrastructure have been proposed and best one chosen using appropriately defined criteria. The proposed configurations were evaluated from the aspect of traffic performances, suitability for forecasted future traffic demand, and vehicle emissions. The obtained results prove the effectiveness of the presented methodology in reducing delays and vehicle emissions and significantly improving the level of service of the chosen use case.
A short, robust brain activation control task optimised for pharmacological fMRI studies
Authors: Harvey Jessica-Lily , Demetriou Lysia , McGonigle John , Wall Matthew B. 
Published: September 2018

Background
Functional magnetic resonance imaging (fMRI) is a popular method for examining pharmacological effects on the brain; however, the BOLD response is dependent on intact neurovascular coupling, and potentially modulated by a number of physiological factors. Pharmacological fMRI is therefore vulnerable to confounding effects of pharmacological probes on general physiology or neurovascular coupling. Controlling for such non-specific effects in pharmacological fMRI studies is therefore an important consideration, and there is an additional need for well-validated fMRI task paradigms that could be used to control for such effects, or for general testing purposes.

Methods
We have developed two variants of a standardized control task that are short (5 minutes duration) simple (for both the subject and experimenter), widely applicable, and yield a number of readouts in a spatially diverse set of brain networks. The tasks consist of four functionally discrete three-second trial types (plus additional null trials) and contain visual, auditory, motor and cognitive (eye-movements, and working memory tasks in the two task variants) stimuli. Performance of the tasks was assessed in a group of 15 subjects scanned on two separate occasions, with test-retest reliability explicitly assessed using intra-class correlation coefficients.

Results
Both tasks produced robust patterns of brain activation in the expected brain regions, and region of interest-derived reliability coefficients for the tasks were generally high, with four out of eight task conditions rated as ‘excellent’ or ‘good’, and only one out of eight rated as ‘poor’. Median values in the voxel-wise reliability measures were also >0.7 for all task conditions, and therefore classed as ‘excellent’ or ‘good’. The spatial concordance between the most highly activated voxels and those with the highest reliability coefficients was greater for the sensory (auditory, visual) conditions than the other (motor, cognitive) conditions.

Discussion
Either of the two task variants would be suitable for use as a control task in future pharmacological fMRI studies or for any other investigation where a short, reliable, basic task paradigm is required. Stimulus code is available online for re-use by the scientific community.
Data challenges of biomedical researchers in the age of omics
Authors: Garcia-Milian Rolando , Hersey Denise , Vukmirovic Milica , Duprilot Fanny 
Published: September 2018

Background
High-throughput technologies are rapidly generating large amounts of diverse omics data. Although this offers a great opportunity, it also poses great challenges as data analysis becomes more complex. The purpose of this study was to identify the main challenges researchers face in analyzing data, and how academic libraries can support them in this endeavor.

Methods
A multimodal needs assessment analysis combined an online survey sent to 860 Yale-affiliated researchers (176 responded) and 15 in-depth one-on-one semi-structured interviews. Interviews were recorded, transcribed, and analyzed using NVivo 10 software according to the thematic analysis approach.

Results
The survey response rate was 20%. Most respondents (78%) identified lack of adequate data analysis training (e.g., R, Python) as a main challenge, in addition to not having the proper database or software (54%) to expedite analysis. Two main themes emerged from the interviews: personnel and training needs. Researchers feel they could improve data analyses practices by having better access to the appropriate bioinformatics expertise, and/or training in data analyses tools. They also reported lack of time to acquire expertise in using bioinformatics tools and poor understanding of the resources available to facilitate analysis.

Conclusions
The main challenges identified by our study are: lack of adequate training for data analysis (including need to learn scripting language), need for more personnel at the University to provide data analysis and training, and inadequate communication between bioinformaticians and researchers. The authors identified the positive impact of medical and/or science libraries by establishing bioinformatics support to researchers.