Miracle-dz/UniFAR-FTUs huggingface dataset:
Citations to highly-cited researchers by their co-authors and their self-citations: How these factors affect highly-cited researchers' h-index in Scopus

Background- The h-index was introduced by Hirsch to quantify an individual’s scientific research output. It has been widely used in different fields to show the relevance of the research work of prominent scientists. But, does h-index really show this relevance? This research is to investigate citing to highly-cited researchers by their co-authors, as well as, highly-cited researchers’ self-citation in three disciplines of knowledge: clinical medicine, computer science, and economics & business; then, we want to evaluate the impact of these two elements on their h-index in Scopus database. Methodology- In this research, highly-cited researchers were selected, in three disciplines, from http://www.isihighlycited. com. Finally 999 highly-cited researchers in those three disciplines were selected (280 authors in clinical medicine, 373 authors in computer science, and 346 authors in economics & business) as our population. After using Excel for primitive calculating and descriptive statistics, SPSS 16.0 was used for inferential statistics; these tests included: T-test, ANOVA test, Correlation test, and Regression test. Findings- The results show that the average of self-citation and co-author citation in clinical medicine is more than computer science, and in computer science is more than economics & business. In these three disciplines, the results show that there is a positive correlation between self-citation and total citations (P<0.01). Also, in these three disciplines, the results show that there is a positive correlation between “co-author citation” and total citations (P<0.01). The results show that there is a positive correlation between self-citation and h-index of highly-cited researchers as well as co-author citation and h-index of highly-cited researchers in three disciplines. Conclusion- It’s seen that there is a various self-citation behavior and co-author citation behavior in different disciplines which relates to subject context. But co-author citation is not under control and represents scientific communications. Although the number of citations do not increase by rising the number of authors, but co-author citation increases by rising the number of co-authors. We suggest that self-citation does not exclude for calculating h-index. It’s better that h-index remains in status quo for highly-cited researchers but for lowly-cited researchers h-index should be modified.
Dynamic relationship and event discovery

This paper studies the problem of dynamic relationship and event discovery. A large body of previous work on relation extraction focuses on discovering predefined and static relationships between entities. In contrast, we aim to identify temporally defined (e.g., co-bursting) relationships that are not predefined by an existing schema, and we identify the underlying time constrained events that lead to these relationships. The key challenges in identifying such events include discovering and verifying dynamic connections among entities, and consolidating binary dynamic connections into events consisting of a set of entities that are connected at a given time period. We formalize this problem and introduce an efficient end-to-end pipeline as a solution. In particular, we introduce two formal notions, global temporal constraint cluster and local temporal constraint cluster, for detecting dynamic events. We further design efficient algorithms for discovering such events from a large graph of dynamic relationships. Finally, detailed experiments on real data show the effectiveness of our proposed solution.
Application of Neural Network-Based Oxide Deposition Models to CMP Modeling

Numerous deposition processes are used in modern semiconductor manufacturing, including high-density plasma chemical vapor deposition (HDP-CVD), spin-on dielectric (SOD), ﬂowable CVD (FCVD), and enhanced high aspect ratio processes (eHARP). Generation of high quality post-deposition surface proﬁles is crucial for chemical-mechanical planarization (CMP) model building, due to the complex nature of the CMP process and long-range effects in CMP. Measurements show complicated post-deposition surface proﬁle height dependence on the underlying pattern for these deposition processes. While high-quality compact models exist for HDP-CVD and SOD processes, building compact models for FCVD and eHARP is a challenge, since they include several deposition and annealing steps, and show complicated behavior width respect to the underlying pattern. In this paper, we present the application of neural networks (NNs) to post-deposition surface proﬁles modeling for the above-mentioned deposition processes. Experiments showed that NNs should have at least two hidden layers and 6–10 neurons per hidden layer to capture the complexity of deposited surface proﬁles. The application of NNs to modeling surface proﬁles of deposition processes has shown that NNs provide a general approach for modeling surface proﬁles of deposition processes without long-range effects for CMP modeling, irrespective of the complexity of the deposition process. of the present research shows that the application of NNs for modeling proﬁles of can any the application of a are open
An implementation of differential evolution algorithm for a single product and single period multi-echelon supply chain network model

In this paper, five variants of Differential Evolution (DE) algorithms are proposed to solve the multi-echelon supply chain network optimization problem. Supply chain network composed of different stages which involves products, services and information flow between suppliers and customers, is a value-added chain that provides customers products with the quickest delivery and the most competitive price. Hence, there is a need to optimize the supply chain by finding the optimum configuration of the network in order to get a good compromise between several objectives. The supply chain problem utilized in this study is taken from literature which incorporates demand, capacity, raw-material availability, and sequencing constraints in order to maximize total profitability. The performance of DE variants has been investigated by solving three stage multi-echelon supply chain network optimization problems for twenty demand scenarios with each supply chain settings. The objective is to find the optimal alignment of procurement, production, and distribution while aiming towards maximizing profit. The results show that the proposed DE algorithm is able to achieve better performance on a set of supply chain problem with different scenarios those obtained by well-known classical GA and PSO.
Effect of dimethyl carbonate on the micromorphology and structure of combustion particles from diesel engines

ABSTRACT Particulate matter emitted by internal combustion engines is one of the main sources of air pollution. Oxygenated fuels can partially replace diesel fuel in combustion and reduce the emission level, especially the particulate matter emitted by diesel engines. In this paper, the emitted particles from the combustion of dimethyl carbonate (DMC)/diesel blends with different blending ratios were collected, and the effects of DMC on the morphology of the diesel particles were analyzed via scanning electron microscopy and small-angle X-ray scattering (SAXS) with a synchrotron radiation source. By studying the small-angle scattering intensity, particle size distribution, fractal dimension, and interface thickness of DMC/diesel combustion particles, the effects of DMC on the degree of agglomeration of particles, particle size distribution, and surface roughness were investigated. The results showed that as the DMC blending ratio increased, the radius of gyration of the particles decreased, the particle size of the primary carbon particles formed by combustion decreased, and the particle size distribution became narrower. With increasing DMC blending ratio, the electron density differences in the particles gradually decreased, the statistical average distance between the particles decreased, the fractal dimension increased, the degree of agglomeration increased, and the structural arrangement was more compact. SAXS analysis revealed that the combustion particles exhibited surface fractal characteristics at a wide angle range and exhibited mass fractal characteristics at a small angle range. The surface fractal dimension and mass fractal dimension of the particles were both higher than those of diesel particles, indicating that the surface roughness, irregularity, and degree of agglomeration of the particles all increased.
Sequencing-based phylogenetic-study of Babesia spp detected in tick tissues in Al-Diwaniyah province, Iraq

Our study purpose was to investigate the evolution of Babesia spp isolated from tissues of ticks that were found on 150 cows in Al-Diwaniyah province, Iraq. To fulfill the required purpose, sampling of 10 ticks was performed from each infested cow. These obtained ticks were morphologically recognized first, and then they were introduced to Lab investigation that was started with crushing the tick tissues to extract the genomic DNA of the Babesia spp. The DNA was then applied to polymerase chain reaction (PCR) method to recognize the amplification of the region that is related to the 18S rRNA gene. The resulted-amplified products were sequenced for the purpose of confirming and doing the phylogenetic analyses. Here, our study has demonstrated 2 different species according to the results of the sequencing and the phylogenetic analyses of the tested Babesisa species. These 2 species are SP1 and SP2. When the phylogenetic tree was built up, the results showed that SP1 and SP2 are closely related to Babesia bovis (HQ264126.1), an isolate from Texas, USA. Our study indicates interesting and valued data that could be used to study various aspects of the tick, Babesia species, and their control in Al-Diwaniyah City, Iraq.
Age threshold for vascular prophylaxis by aspirin in patients without diabetes

Objective: To determine an appropriate age threshold at which to prescribe aspirin for primary cardiovascular disease (CVD) prevention among men and women without diabetes. Design: Cross-sectional study. Setting: 304 general practices in England and Wales contributing to The Health Improvement Network (THIN) electronic patient files. Participants: Subjects aged between 30 and 75 years without diabetes, not prescribed any lipid-lowering treatment and with no previous history of CVD. Subjects had to have been registered by their practices for the whole of the preceding 12 months to be included in the analysis. Outcomes measures: Relation between age and coronary heart disease (CHD) risk, and the age threshold at which subjects without diabetes develop an estimated 10-year CHD risk of ⩾10%. Results: The age transition from <10% to >10%, 10-year CHD risk for men and women without diabetes occurred at ages 47.8 for men and 57.3 for women. Conclusions: In the absence of significant bleeding risks, aspirin should routinely be considered for all men and women without diabetes above the ages of 48 and 57 years, respectively, for primary CVD prevention. For subjects below these age thresholds or for those above the age of 75 years, the decision to initiate aspirin should be based on a patient’s individual cardiovascular risk profiles. These proposed age thresholds aim to take into account a patient’s gender, bleeding risk and the cardioprotective benefits of low-dose aspirin treatment.
The perceived impact of privatization on local health departments.

OBJECTIVES This article presents nationally representative data on the effects of privatization on local health departments (LHDs). METHODS A stratified representative national sample of 380 LHDs was drawn from a national list of 2488 departments. Telephone interviews were conducted with 347 LHD directors. RESULTS One half of the directors of LHDs with privatized services reported that privatization helped the performance of core functions. Privatization often resulted in increased time needed for management and administration. More than a third of LHD directors reported concern about loss of control over the performance of privatized functions and services. CONCLUSIONS Privatization is part of a broader shift toward "managing" rather than directly providing public health services, yet privatization often reduces LHDs' control over the performance of services.
A Metamodel-Based Approach to Information Systems Evolution and Data Migration

The potential impact of model-driven engineering is considerable, and far extends beyond the initial development and delivery of a system. The automatic generation of systems from abstract models also facilitates evolution: the definitive description of structure and behaviour remains accessible, and changes are more easily planned and accommodated. Within the domain of information systems, this is useful only if the data held in the system can be migrated easily to the next version. This paper shows how migration can be facilitated by means of a metamodelling approach, in which a separate model of changes is used as a basis for the automatic generation of semantics-preserving, platform-specific data transformations.
Design and Analysis of a New Flux Memory Doubly Salient Motor Capable of Online Flux Control

In this paper, a new type of memory motor, namely flux memory doubly salient motor, is proposed and tested. The key is to incorporate both the online tunable permanent magnets (PMs) and magnetizing windings into a stator-permanent-magnet motor. Thus, the resulting new memory motor can offer effective and efficient flux control. The design method of the memory motor is presented in detail. By combining a piecewise-linear hysteresis model with the finite element method, the static and transient electromagnetic performances are investigated. Experimental results of the prototype are given to verify the validity of the proposed motor.
An Examination of Trust Effects and Pre-Existing Relational Risks in eGovernment Services

This study brings to attention distinct characteristics of government-citizen relationships that should be addressed when modeling citizens' G2C service usage behavior and calls for an e-government user acceptance model. Earlier studies on G2C service adoption have shown that private sector-oriented models can result in inconsistent findings when applied to different service types or circumstances. This paper argues that government-citizen relationships often go beyond underlying assumption of user acceptance models applied across different areas, and that a more generalizable model for various e-government services is essential for understanding and improving citizens' e-government service acceptance. This argument is further developed by an empirical examination of a government-citizen relationship where use of an e-government service requires citizens to transmit highly sensitive information, but trustworthiness of the authority does not affect citizens' use of the service.
The factor structure of the Mystical Experience Questionnaire (MEQ): Reply to Bouso et al., 2016

Recent medical research on classic psychedelic substances (e.g., psilocybin, LSD, and ayahuasca) has utilized a number of questionnaires to assess the subjective effects of psychedelics, but only a few of these questionnaires have undergone analysis with modern psychometric methods (Barrett, Johnson, & Griffiths, 2015; MacLean, Leoutsakos, Johnson, & Griffiths, 2012; Nour, Evans, Nutt, & Carhart‐Harris, 2016; Studerus, Gamma, & Vollenweider, 2010). The psychometric properties of three psychedelic effects questionnaires (the Hallucinogen Rating Scale or HRS, the Mystical Experience Questionnaire or MEQ, and the Addiction Research Center Inventory or ARCI) were recently investigated in a sample of individuals who had participated in an ayahuasca ceremony (Bouso, Pedrero‐Perez, Gandy, & Alcazar‐Corcoles, 2016). The factor structures of the HRS and ARCI were found to differ from the factor structures originally proposed for those scales. The factor structure of the MEQ was found to roughly match the four‐ factor structure identified in large‐sample (n1=1602, n2=440) online surveys (MacLean et al., 2012) and a smaller sample (n=184) of experimental laboratory data (Barrett et al., 2015) with psilocybin; however, Bouso and colleagues suggested that an alternate two‐factor structure for the MEQ was most appropriate. We are grateful that Bouso and colleagues have drawn attention to the importance of psychometrics in psychedelic research, and we applaud their efforts. It is clear that the HRS and ARCI have serious flaws that need to be addressed. However, we ask readers to consider the proposed two‐factor MEQ30 structure with caution, especially in cases where conditions for mystical experience (dose, set, and setting) are optimized. It is known that MEQ scores in controlled experimental psilocybin studies are dose‐dependent (Griffiths et al., 2011) and the MEQ was psychometrically validated using data collected after laboratory administration of a high dose of psilocybin (Barrett et al., 2015) or in reference to a profound or mystical experience with psilocybin (MacLean et al., 2012). While the median drug intensity of ayahuasca experiences reported by Bouso and colleagues was a “moderate” experience (from three response options, including “low”, “moderate”, and “high”), this designation is ambiguous and quite likely represents a very wide range of experiences, many of which may not be expected to occasion a mystical experience, or even come close. Low representation of high‐dose experiences in this sample may limit the generalizability of the two‐factor structure that Bouso reports. It is clear that the MEQ factor structure may vary in different settings. It may be the case that the MEQ30 has a different psychometric
Distribution of Water Channel Protein RWC3 and Its Regulation by GA and Sucrose in Rice ( Oryza sativa )

Water channel proteins facilitate water flux across cell membranes and play important roles in plant growth and development. By GUS histochemical assay in RWC3 promoter-GUS transgenic rice (Oryza sativa L. cv. Shenxiangjin 4), one of the members of water channel proteins in rice, RWC3, was found to distribute widely in variety of organs, from vegetative and reproductive organs. Further studies showed that gibberellin (GA) enhanced the GUS activity in the transgenic calli, suspension cells and leaves, whereas ancymidol (anc), an inhibitor of GA synthesis, reduced the GUS activity. Sucrose was found to inhibit the effects induced by addition of GA, suggesting a possible cross-talk between GA and sucrose signaling on regulation of the RWC3 gene expression.
Drosophila adult muscle precursor cells contribute to motor axon pathfinding and proper innervation of embryonic muscles

Adult Muscle Precursors (AMPs), the Drosophila muscle stem cells, arise from the asymmetric cell divisions of a subset of muscle progenitors ([1]) and are characterized by the persistent expression of the myogenic transcription factor Twist ([2]) and activation of the Notch pathway ([3]; [4]). They occupy stereotyped positions in the vicinity of developing body wall muscles, stay quiescent and undifferentiated during embryonic life and are reactivated during second larval instar ([5]; [6]) to generate muscles of the adult fly. Strikingly, AMPs are also located in the path of intersegmental (ISN) and segmental (SN) motor neuron branches ([2]; [7]). However, their role and interactions with the motor neurons have not yet been analyzed in details. Here, using AMP sensor line revealing cell membrane extensions we show that the navigating ISN first contacts the dorso-lateral (DL-AMPs) and then the dorsal AMP (D-AMP) marking the end of its trajectory. In parallel, the segmental nerve SNa innervating lateral muscles targets the lateral AMPs (L-AMPs). In vivo analyses of AMPs behavior highlight an active filopodial dynamic of AMPs toward the ISN and SNa suggesting they could guide motor axons and contribute to muscle innervations. Indeed, our data show that loss or mispositioning of L-AMPs affect the SNa motor axons pathfinding and branching, leading to loss or aberrant muscle innervation. The finding of a transient expression of the guidance molecule Sidestep in L-AMPs suggests its implication in this process. Thus, proper muscle innervation does not only rely on the dialogue between the motor neurons and the muscles, but also on the AMP cells. AMPs represent spatial landmarks for navigating motor neurons and their positioning is critical for the muscles innervation in the lateral region.
ANGEL-Machine Learning Classification

The Automated Network Games Enhancement Layer (ANGEL) project aims to leverage machine learning techniques to automate the classification and isolation of interactive (e.g. games, voice over IP) and noninteractive (e.g. web) traffic. This information is then used to dynamically reconfigure the network to improve the Quality of Service provided to the current interactive traffic flows and subsequently deliver improved performance to the end users. In this document we first describe the current solutions for network traffic classification and their shortfalls. Then we present the novel approach of classifying network traffic flows based on machine learning techniques and statistical flow attributes such as packet length and interarrival time statistics. We evaluate if a machine learning based approach meets the accuracy and performance requirements of the ANGEL architecture and select appropriate machine learning algorithms. The evaluation is based on results obtained for real game traffic captured in the network.
Velocity Analysis of Multi-Receiver Full Waveform Acoustic Logging Data In Open and Cased Holes

Average semblance and maximum-likelihood spectral analyses are applied to synthetic and field full waveform acoustic logging data to determine formation velocities. Of particular interest is the ability of these methods to resolve the P and shear/pseudoRayleigh arrivals in data from poorly-bonded cased boreholes. In synthetic open-hole data the velocity analyses yield results within 4% of the true velocities. Results from synthetic well-bonded cased hole data are generally as good as those from the open hole data. However, if the formation P-wave velocity is within roughly 10% of the plate velocity of the steel pipe (about 5.3-5.5 km/s), then there may be a resonance effect that appears to slow down the P wave slightly (on the order of 6%). For cased-hole models with no steel/cement bonding (the free-pipe situation), the measured P-wave velocities are typically 6 to 8% less than the actual formation velocities. If the formation S-wave velocity is greater than about 2.5 km/s, the S-wave velocity estimate may also be 6 to 8% low. Furthermore, increasing the thickness of either the cement layer or the fluid layer between the pipe and the cement further decreases the formation velocity estimates. Also, if the P-wave velocity is within roughly 15% of the velocity of the steel arrival, the P wave may not be resolved by the semblance method unless the data is first low-pass filtered. Initial tests show that this filtering process may adversely affect the final P-wave velocity estimate, but the details of this type of approach have not been studied. The P wave is resolved. by spectral analysis of the original, nnfiltered data. For cased-hole models with no cement/formation bonding (the unbonded-casing 366 Block et al. situation), formation S-wave velocities are estimated to within 3% relative error, and the formation P-wave velocity is estimated to within 2% error in a slow formation. However, for P-wave velocities between 3.4 km/s and 5.94 km/a, the P wave cannot be resolved by spectral analysis, and it is resolved by the semblance method only in the model with the low velocity (3.4 km/s).