Miracle-dz/UniFAR-FTUs huggingface dataset:
Metrics of Scholarly Impact

Assessments of scientific contribution are important for a variety of reasons. For individuals early in their career, metrics of scientific work can provide valuable feedback about where they stand and the progress they have made. For departmental faculty seeking to hire a new member, such metrics can simplify the task of wading through hundreds of applications to identify a subset of applicants whom they might wish to interview. For departmental chairs, these metrics may influence annual raises and the allocation of limited resources. For university administrators, these metrics help identify faculty who warrant promotion and tenure, and departments that warrant concern. For scientific societies, these metrics influence the selection of award recipients across the course of careers. For public and private funding agencies, assessments of science help identify areas of progress and vitality that may warrant support as well as a means of documenting performance, ensuring accountability, and evaluating the return on their research investment. Measures of science can also be used for a variety of other purposes, such as to identify the structure of science, impact of academic journals, influential fields of research, and factors that may contribute to the likelihood of discoveries. Ruscio and colleagues (Ruscio, Seaman, D’Oriano, Stremlo, & Mahalchik, this issue) provide a thoughtful empirical analysis of 22 different measures of individual scholarly impact. The simplest metric is number of publications, which Simonton (1997) found to be a reasonable predictor of career trajectories. There are numerous variants on this metric, such as the number of peer-reviewed articles, the number of first-authored publications, the number of articles published in a specific premier journal in a field, the number of articles without more-senior collaborators, and the number of publications across years (publication trajectories). Although the assessment of the scholarly contribution of a candidate for tenure is unlikely to be favorable if there are no or very few scientific publications, the number of publications is a far-from-perfect index of scientific contribution. Moreover, the incentives created by a metric such as number of publications may not promote the quality, innovativeness, programmatic nature, and cumulative impact of the research. Ruscio et al. (this issue), therefore, used five criteria to evaluate metrics of science: (1) ease of understanding, (2) accuracy of calculation, (3) effects of incentives, (4) influence of extreme scores, and (5) validity. Given the computational aids available today, the first 2 metrics are perhaps the least important and the third and fifth are most important. Most of the indices examined by Ruscio et al. (this issue) are based on citation data, which may provide a better incentive structure for scientific contribution than simple publication counts.
Glass Ionomer Cement Release of the Fluoride as Anti-Cariogenic Properties among Four Different Types . Comparative Evaluation

Purpose: The aim of this study was to evaluate the anti-cariogenic property (Fluoride ion release and its antibacterial properties) among four types of glass ionomer cements used as a permanent filling of caries cavities. Materials and Methods: Four types of glass ionomer cements were used in this study. [1] Fuji IX (GC, Japan); Conventional glass-ionomer cement, [2] Fuji II LC (GC, Japan); Resin-modified glass ionomer cement (RMGIC), [3] Dyract AP (Dentsply, Konstanz, Germany); Polyacid-modified composite resin (compomer) and [4] Ketac N100 (3M ESPE St. Paul, MN, USA); Nano-filled resin-modified GIC. The antibacterial activity of each material was evaluated against the Streptococcus mutans after day 2,7,14 and 30. Results: All types of GIC restorative materials developed antibacterial activity but decreased depending increased the tested time. Conclusion: The best one developed antibacterial activity was Fuji IX (GC, Japan); Conventional glass-ionomer cement followed by Ketac N100 (3M ESPE St. Paul, MN, USA); Nano-filled resin-modified GIC while the least one was Dyract AP (Dentsply, Konstanz, Germany); Polyacid-modified composite resin (compomer).
Automated Essay Scoring Versus Human Scoring: A Comparative Study

The current research was conducted to investigate the validity of automated essay scoring (AES) by comparing group mean scores assigned by AES and human raters. Data collection included two standardized writing tests – WritePlacer Plus and the Texas Higher Education Assessment (THEA) writing test. The research sample of 107 participants was drawn from a Hispanic serving institution in South Texas. The One-Way Repeated-Measures ANOVA and the follow-up Paired Samples t test were conducted to examine the group mean differences. Results of the tests indicated that the mean score assigned by IntelliMetric™ was significantly higher than faculty human raters’ mean score on WriterPlacer Plus test, and IntelliMetric™ mean score was also significantly higher than THEA mean score assigned by human raters from National Evaluation Systems. A statistically significant difference also existed between the human raters’ mean score on WritePlacer Plus and human raters’ mean score on THEA. These findings did not corroborate previous studies that reported non-significant mean score differences between AES and human scoring.
A clustering-based method for single-channel fetal heart rate monitoring

Non-invasive fetal electrocardiography (ECG) is based on the acquisition of signals from abdominal surface electrodes. The composite abdominal signal consists of the maternal electrocardiogram along with the fetal electrocardiogram and other electrical interferences. These recordings allow for the acquisition of valuable and reliable information that helps ensure fetal well-being during pregnancy. This paper introduces a procedure for fetal heart rate extraction from a single-channel abdominal ECG signal. The procedure is composed of three main stages: a method based on wavelet for signal denoising, a new clustering-based methodology for detecting fetal QRS complexes, and a final stage to correct false positives and false negatives. The novelty of the procedure thus relies on using clustering techniques to classify singularities from the abdominal ECG into three types: maternal QRS complexes, fetal QRS complexes, and noise. The amplitude and time distance of all the local maxima followed by a local minimum were selected as features for the clustering classification. A wide set of real abdominal ECG recordings from two different databases, providing a large range of different characteristics, was used to illustrate the efficiency of the proposed method. The accuracy achieved shows that the proposed technique exhibits a competitve performance when compared to other recent works in the literature and a better performance over threshold-based techniques.
Some q‐rung orthopair fuzzy Heronian mean operators in multiple attribute decision making

The generalized Heronian mean and geometric Heronian mean operators provide two aggregation operators that consider the interdependent phenomena among the aggregated arguments. In this paper, the generalized Heronian mean operator and geometric Heronian mean operator under the q‐rung orthopair fuzzy sets is studied. First, the q‐rung orthopair fuzzy generalized Heronian mean (q‐ROFGHM) operator, q‐rung orthopair fuzzy geometric Heronian mean (q‐ROFGHM) operator, q‐rung orthopair fuzzy generalized weighted Heronian mean (q‐ROFGWHM) operator, and q‐rung orthopair fuzzy weighted geometric Heronian mean (q‐ROFWGHM) operator are proposed, and some of their desirable properties are investigated in detail. Furthermore, we extend these operators to q‐rung orthopair 2‐tuple linguistic sets (q‐RO2TLSs). Then, an approach to multiple attribute decision making based on q‐ROFGWHM (q‐ROFWGHM) operator is proposed. Finally, a practical example for enterprise resource planning system selection is given to verify the developed approach and to demonstrate its practicality and effectiveness.
Migrating Learning Management Systems: A Case of a Large Public University

In the past 20 years, institutions of higher education have made major investments in Learning Management Systems (LMSs). As institutions have integrated the LMS into campus culture, the potential of migrating to not only an upgraded version of the LMS, but also an entirely different LMS, has become a reality. This qualitative research study examines the perspectives of five stakeholders involved with the migration of an LMS at a major research institution in the southeastern United States. Using Lewin’s (1947) Change Management Model and Enterprise Resource Planning (ERP) Model as analogies, this research seeks to understand the role and responsibilities of the various stakeholders, their decision-making, and the implications of the decisions on the migration process. Using Glaser and Strauss’s (1967) constant comparative method and Charmaz’s (2006) work related to grounded theory, four major categories emerged from our data: time as a catalyst for change, power of communication, compatibility of technologies, and faith in the system. The categories contribute to a preliminary model that may assist other institutions as they consider whether to migrate LMSs.
Real-Time Anomaly Detection in Elderly Behavior

The rapid growth of the aging population and the increasing cost of the hospitalization are arousing the urgent need of the remote health monitoring system. Using the physiological sensing devices enable early detecting of health issues and allow for prompt treatment to help elderly towards changing their anomalous behavior and having a healthy lifestyle. Our approach, exploited task models to produce scenarios (which is the expected user behavior) and a middleware software, Context Manager to detect the events happened in the real context. Later, our real-time algorithm compares the expected user behavior to the real one detected in user context to find the anomalies if there is any. Finally, we validated our approach via a simulator, which automatically generates the anomalous sequences of user activities. The experimental results show that our system can detect abnormal user behavior precisely and effectively. Besides, the system should be able to generate proper action based on the detected deviation to motivate older people towards a healthy lifestyle.
Recent progress on lower hybrid current drive and implications for ITER

The sustainment of steady-state plasmas in tokamaks requires efficient current drive systems. Lower hybrid current drive is currently the most efficient method to generate a continuous additional off-axis toroidal plasma current and to reduce the poloidal flux consumption during the plasma current ramp-up phase. The operation of the Tore Supra ITER-like lower hybrid (LH) launcher has demonstrated the capability to couple LH power at ITER-like power densities with very low reflected power during long pulses. In addition, the installation of eight 700 kW/CW klystrons at the LH transmitter has allowed increasing the total LH power in long-pulse scenarios. However, in order to achieve pure stationary LH-sustained plasmas, some R&D is needed to increase the reliability of all the systems and codes, from radio-frequency (RF) sources to plasma scenario prediction. The CEA/IRFM is addressing some of these issues by leading a R&D programme towards an ITER LH system and by the validation of an integrated LH modelling suite of codes. In 2011, the RF design of a mode converter was validated at a low power. A 500 kW/5 s RF window is currently under manufacture and will be tested at a high power in 2012 in collaboration with the National Fusion Research Institute. All of this work aims to reduce the operational risks associated with the ITER steady-state operations.
A new linear Poisson-Boltzmann equation and finite element solver by solution decomposition approach

The linear Poisson-Boltzmann equation (LPBE) is one well-known implicit solvent continuum model for computing the electrostatic potential of biomolecules in ionic solvent. To overcome its singular difficulty caused by Dirac delta distributions of point charges and to further improve its solution accuracy, we develop in this paper a new scheme for solving the current LPBE model, a new LPBE model, and a new LPBE finite element program package based on our previously proposed PBE solution decomposition. Numerical tests on biomolecules and a nonlinear Born ball model with an analytical solution validate the new LPBE solution decomposition schemes, demonstrate the effectiveness and efficiency of the new program package, and confirm that the new LPBE model can significantly improve the solution accuracy of the current LPBE model.
Wavelet-based extended morphological profile and deep autoencoder for hyperspectral image classification

In this paper, we propose a novel scheme to learn high-level representative features and conduct classification for hyperspectral image (HSI) data in an automatic fashion. The proposed method is a collaboration of a wavelet-based extended morphological profile (WTEMP) and a deep autoencoder (DAE) (“WTEMP-DAE”), with the aim of exploiting the discriminative capability of DAE when using WTEMP features as the input. Each part of WTEMP-DAE is ingenious and contributes to the final classification performance. Specifically, in WTEMP-DAE, the spatial information is extracted from the WTEMP, which is then joined with the wavelet denoised spectral information to form the spectral-spatial description of HSI data. The obtained features are fed into DAE as the original input, where the good weights and bias of the network are initialized through unsupervised pre-training. Once the pre-training is completed, the reconstruction layers are discarded and a logistic regression (LR) layer is added to the top of the network.
Quantifying an aquifer nitrate budget and future nitrate discharge using field data from streambeds and well nests

Novel groundwater sampling (age, flux, and nitrate) carried out beneath a streambed and in wells was used to estimate (1) the current rate of change of nitrate storage, dSNO3 /dt, in a contaminated unconfined aquifer, and (2) future [ NO3− ]FWM (the flow‐weighted mean nitrate concentration in groundwater discharge) and fNO3 (the nitrate flux from aquifer to stream). Estimates of dSNO3 /dt suggested that at the time of sampling (2013) the nitrate storage in the aquifer was decreasing at an annual rate (mean = −9 mmol/m2yr) equal to about one‐tenth the rate of nitrate input by recharge. This is consistent with data showing a slow decrease in the [ NO3− ] of groundwater recharge in recent years. Regarding future [ NO3− ]FWM and fNO3 , predictions based on well data show an immediate decrease that becomes more rapid after ∼5 years before leveling out in the early 2040s. Predictions based on streambed data generally show an increase in future [ NO3− ]FWM and fNO3 until the late 2020s, followed by a decrease before leveling out in the 2040s. Differences show the potential value of using information directly from the groundwater—surface water interface to quantify the future impact of groundwater nitrate on surface water quality. The choice of denitrification kinetics was similarly important; compared to zero‐order kinetics, a first‐order rate law levels out estimates of future [ NO3− ]FWM and fNO3 (lower peak, higher minimum) as legacy nitrate is flushed from the aquifer. Major fundamental questions about nonpoint‐source aquifer contamination can be answered without a complex numerical model or long‐term monitoring program.
Graph-Based Reflectance Segmentation

Most of the unsupervised image segmentation algorithms use just RGB color information in order to establish the similarity criteria between pixels in the image. This leads in many cases to a wrong interpretation of the scene since these criteria do not consider the physical interactions which give raise to of those RGB values (illumination, geometry, albedo) nor our perception of the scene. In this paper, we propose a novel criterion for unsupervised image segmentation which not only relies on color features, but also takes into account an approximation of the reﬂectance properties of the materials. By using a perceptually uniform color space, we apply our criterion to one of the most relevant state of the art segmentation techniques, showing its suitability for segmenting images into small and coherent clusters of constant reﬂectance. Furthermore, due to the wide adoption of such algorithm, we provide for the ﬁrst time in the literature an evaluation of this technique under several scenarios and different conﬁgurations of its parameters. Finally, in order to enhance both the accuracy of the segmentation and the inner coherence of the clusters, we apply a series of image processing ﬁlters to the input image (median, shift-median, bilateral), analyzing their effects in the segmentation process. Our results can be transferred to any image segmentation algorithm.
Clockwise-directional circle swimmer moves counter-clockwise in Petri dish- and ring-like confinements

A self-propelled rod which is driven by a constant internal force and torque performs circular motion in two spatial dimensions with an “internal” radius governed by the torque-to-force ratio and is referred to as a circle swimmer. Using analytical methods and computer simulations, we study the Brownian dynamics of a circle swimmer in a confining Petri dish- or ring-shaped geometry and compute the mean of the swimmer's position, its steady-state properties and its orientational motion. For small torque-to-force ratios, the confinement inverts the orientational sense of the motion: a clockwise-directional circle swimmer moves counter-clockwise in the confinement. Our results are verifiable for self-propelled colloidal rods, for vibrated granular rods and for motile bacteria in cylindrical confinements.
COMPUTATIONAL IDENTIFICATION OF miRNAs AND THEIR TARGETS FROM CROCUS SATIVUS L.

miRNAs are smaller known entities that perform several crucial regulatory roles in plants. Identification and characterization of miRNAs has been a challenging task which has become simplified with the development of com- putational approaches. In the present study, three novel miRNAs were predicted from Crocus sativus by computational approaches. A total 6767 ESTs were mined from the EST database available at NCBI. The software MicroPC was utilized which resulted with the prediction of three miRNAs, csa-miR1, csa-miR2 and csa-miR3. Targets were predicted for the respective miRNAs using the miRU2 program. The identified targets have a role in plant growth, senescence, disease re- sistance and various stress responses. In addition, some targets are involved in mRNA export, protein synthesis and post- translational modifications.
Snow cover sensitivity to black carbon deposition in the Himalayas: from atmospheric and ice core measurements to regional climate simulations

Abstract. We applied a climate-chemistry global model to evaluate the impact of black carbon (BC) deposition on the Himalayan snow cover from 1998 to 2008. Using a stretched grid with a resolution of 50 km over this complex topography, the model reproduces reasonably well the remotely sensed observations of the snow cover duration. Similar to observations, modelled atmospheric BC concentrations in the central Himalayas reach a minimum during the monsoon and a maximum during the post- and pre-monsoon periods. Comparing the simulated BC concentrations in the snow with observations is more challenging because of their high spatial variability and complex vertical distribution. We simulated spring BC concentrations in surface snow varying from tens to hundreds of μg kg −1 , higher by one to two orders of magnitude than those observed in ice cores extracted from central Himalayan glaciers at high elevations (>6000 m a.s.l.), but typical for seasonal snow cover sampled in middle elevation regions ( −2 leading to a localised warming between 0.05 and 0.3 °C.
Pancytopenia Associated with Hypopituitarism in an Acromegaly Patient: A Case Report and a Review of the Literature

We present the case of a patient with acromegaly who had pancytopenia with hypopituitarism secondary to the excision of a pituitary macroadenoma and radiation therapy. A 28-year-old man presented with pancytopenia and serum electrolyte abnormalities. He was diagnosed with acromegaly and underwent surgery and gamma-knife radiotherapy for a pituitary macroadenoma at the age of 22 years. A recent brain magnetic reso nance imaging showed an empty sella, and the basal hormonal profile demonstrated deficiencies of pituitary hormones except thyrotropin. As presenting pancytopenia, his bone marrow biopsy showed hypocellular marrow. The total number of hemocytes increased after hydrocortisone replacement. Hypopituitarism was a possible cause of pan cytopenia, and glucocorticoids had crucial effects on converting pancytopenia to normal in this case. ( Endocrinol Metab 27:308313, 2012)
Carbonate chemistry in sediment pore waters of the Rhône River delta driven by early diagenesis (NW Mediterranean)

The Rhône River is the largest source of terrestrial organic and inorganic carbon for the Mediterranean Sea, and a large fraction thereof is buried or mineralized in the sediments close to the river mouth. The mineralization follows aerobic and anaerobic pathways with varying impacts on the 10 carbonate chemistry in the sediment pore waters. This study focused on the production of dissolved inorganic carbon (DIC) and total alkalinity (TA) by early diagenesis at the sediment water-interface, consequential pH variations and the effect on calcium carbonate precipitation or dissolution. The sediment pore water chemistry was investigated during the DICASE cruise along a transect from the Rhône River outlet to the continental shelf. The concentrations of DIC, TA, SO 42- and Ca 2+ were 15 analyzed on bottom waters and extracted pore waters, whereas pH and oxygen concentrations were measured in situ using microelectrodes. The average oxygen penetration depth into the sediment was 1.7 ± 0.4 mm in the proximal domain and 8.2 ± 2.6 mm in the distal domain, indicating intense aerobic respiration rates. Diffusive oxygen fluxes through the sediment water interface range between 3 and 13 mmol O 2 m -2 d -1 . The DIC and TA concentrations increased with depth in the sediment pore waters up 20 to 48 mmol L -1 near the river outlet and up to 7 mmol L -1 on the shelf as a result of aerobic and anaerobic mineralization processes. Due to oxic processes, the pH decreased by 0.6 pH units in the oxic layer carbonate of the a manocalcimeter with uncertainties of 2.5 % of A manocalcimeter in a small, gastight the be acidified with HCl to calcium carbonates. The increase of pressure is measured with a manometer and is directly proportional to the carbonate content of the sediment sample. Sediment samples also been analyzed via X-Ray diffraction on a X-Pert