Miracle-dz/UniFAR-FTUs huggingface dataset:
gcamdata: An R Package for Preparation, Synthesis, and Tracking of Input Data for the GCAM Integrated Human-Earth Systems Model

The increasing data requirements of complex models demand robust, reproducible, and transparent systems to track and prepare models’ inputs. Here we describe version 1.0 of the gcamdata R package that processes raw inputs to produce the hundreds of XML files needed by the GCAM integrated human-earth systems model. It features extensive functional and unit testing, data tracing and visualization, and enforces metadata, documentation, and flexibility in its component data-processing subunits. Although this package is specific to GCAM, many of its structural pieces and approaches should be broadly applicable to, and reusable by, other complex model/data systems aiming to improve transparency, reproducibility, and flexibility. Funding statement: Primary support for this work was provided by the U.S. Department of Energy, Office of Science, as part of research in Multi-Sector Dynamics, Earth and Environmental System Modeling Program. Additional support was provided by the U.S. Department of Energy Offices of Fossil Energy, Nuclear Energy, and Energy Efficiency and Renewable Energy and the U.S. Environmental Protection Agency.
In Silico Validation of ncRNA-ncRNA Interaction Sites with ncRNAs Represented by k-mers Features

A recent catalogue of human transcriptome, namely CHESS database, assembled from RNA sequencing experiments as a part of the Genotype-Tissue Expression (GTEx) Project reported more non-coding RNA genes (21,856) than protein-coding (21,306), revealing an unexpectedly vast amount of transcriptional noise (Pertea et al, 2018). In this study, we introduce a workflow coded in KNIME that computationally distinguishes the ncRNA-ncRNA interaction sites with less reliable interaction sites containing less experimentally validated binding sites than the interaction sites with more experimental validation. Duplex structure and k-mer features of the ncRNA-ncRNA binding sites with experimental verification were used as input to the classification workflow. In our analysis, we observed that although duplex structure features had no positive effect on the success rate of the classification, using just the k-mer features, ~80% success could be achieved in categorization of the confidence of the ncRNA-ncRNA binding sites. Our result verified the classification performance of miRNA-mRNA targets using only k-mer features from our previous study (Yousef et al, 2018).
Data Optimization on Multi Robot Sensing System with RAM Based Neural Network Method

Monitoring the environment activities is an attractive Abstract— Monitoring the environment activities is an attractive thing for development. That is because the human life would affect the surrounding environtment. There's a lot of research of environment has been done, one of those is the changes of air quality in urban areas. To measure the level of air quality, the data and information from field measurements and laboratory analysis result was needed. This paper review the research result that focus on sensor data processing in multi robot using RAM based neural network. There are 11 pattern input data were processed by temperature data optimization from 250C until 350C, humadity data from 20% until 60% and gas data from 350ppm until 450ppm. The obtained result is from 8 bits and 9 bits become 6 bits in certain level with optimazion percentage is25% and 33,3%. This result effect to the computationan load, it's become more simple, the execution time and data communication becomes faster.
A Trend Analysis of Machine Learning Research with Topic Models and Mann-Kendall Test

— This paper aims to systematically examine the literature of machine learning for the period of 1968~2017 to identify and analyze the research trends. A list of journals from well-established publishers ScienceDirect, Springer, JMLR, IEEE (approximately 23,365 journal articles) related to machine learning is used to prepare a content collection. To the best of our information, it is the first effort to comprehend the trend analysis in machine learning research with topic models: Latent Semantic Analysis (LSA), Latent Dirichlet Allocation (LDA), and LDA with Coherent Model (LDA_CM). The LDA_CM topic model gives the highest topic coherence amongst all topic models under consideration. This study provides a scientific ground that helps to overcome the subjectivity of collective opinion. The Mann-Kendall test is used to understand the trend of the topics. Our findings provide indicative of paradigmatic shifts in research methodology of significant patterns of topical prominence and the evolving research areas. It
Cloud Computing-Positive Impacts and Challenges in Business Perspective

Due to rapid growth of computing resources over the past years, cloud computing has been treated as a prominent research field and this technology appeared as a new solution in the IT field. Many businesses including small, medium and enterprise are migrating to this technology for so many reasons such as computing resources, reduced total cost of ownership, on demand services, increased revenue and many more. Cloud Computing offers number of advantages of cloud migration that motivated the business enterprises to adopt this change. There are so many challenges for the companies adopting cloud computing like interoperability, portability, organizational aspects and the most important challenge is the security and privacy of the information. There are different solutions or suggestions that a company should follow to overcome various challenges and issues
MINIMAL DETECTABLE CHANGE IN FOOT-PRESSURE MEASUREMENTS IN TYPICALLY DEVELOPING CHILDREN

INTRODUCTION: Pedobarography is extensively used to evaluate foot deformities. Unfortunately, little is known about the uncertainty and sources of uncertainty in the pedobarographic data. We need this information to evaluate if observed differences originated from treatment something else like processing. The purpose of this study is to determine the minimal detectable change (MDC) in a variety of foot pressure measures. The MDC is the sum of the net uncertainties (δnet) for each of the two measures being compared plus any inter-rater uncertainty (δinter) if different raters reduced the data. For a given measure, the net uncertainty is determined by the step-to-step uncertainty (δstep2step), the day-to-day uncertainty (δday2day), and the intra-rater uncertainty (δintra). The purpose of this study was to quantify variability in segmented pedobarograph data and thereby estimate the MDC and its component uncertainties as a function of age.
The Roles of Gratification Opportunities, Gratifications-Obtained, and Demographics in Determining Usage Preference of Instant Messaging and E-mail among College Students

In studying media choice, past researches have focused on using gratifications sought and obtained to explain media preference. However, Dimmick and Wallschlaeger (1986) introduced a new construct - gratification opportunities - to supplement the traditional research framework of using “uses and gratifications” in examining motives for media use. Dimmick and Albarran’s (1994) study on media preference found significant contributions from gratification opportunities in determining media choice. Grounded in uses and gratifications and gratification opportunities perspectives, this exploratory research examined (1) the preference of IM and e-mail among college students, (2) the motives college students associated with IM and e-mail use, (3) perceived gratification opportunities from IM and e-mail, (4) how demographics, gratification opportunities and gratifications obtained predict computer-mediated communication preference between instant messaging and e-mail, and (5) to what extend can these factors predict the level of use in IM and e-mail among a group of 236 college students. Data show that 78% of the students’ preferred instant messaging (MSN
Structural and functional characterization of KEOPS dimerization by Pcc 1 and its role in t 6 A biosynthesis

KEOPS is an ancient protein complex required for the biosynthesis of N6-threonylcarbamoyladenosine (t6A), a universally conserved tRNA modification found on all ANN-codon recognizing tRNAs. KEOPS consist minimally of four essential subunits, namely the proteins Kae1, Bud32, Cgi121 and Pcc1, with yeast possessing the fifth essential subunit Gon7. Bud32, Cgi121, Pcc1 and Gon7 appear to have evolved to regulate the central t6A biosynthesis function of Kae1, but their precise function and mechanism of action remains unclear. Pcc1, in particular, binds directly to Kae1 and by virtue of its ability to form dimers in solution and in crystals, Pcc1 was inferred to function as a dimerization module for Kae1 and therefore KEOPS. We now present a 3.4 Å crystal structure of a dimeric Kae1–Pcc1 complex providing direct evidence that Pcc1 can bind and dimerize Kae1. Further biophysical analysis of a complete archaeal KEOPS complex reveals that Pcc1 facilitates KEOPS dimerization in vitro. Interestingly, while Pcc1-mediated dimerization of KEOPS is required to support the growth of yeast, it is dispensable for t6A biosynthesis by archaeal KEOPS in vitro, raising the question of how precisely Pcc1-mediated dimerization impacts cellular biology.
Comparing bags of features, conventional convolutional neural network and AlexNet for fruit recognition

This paper presents a comparative study between Bag of Features (BoF), Conventional Convolutional Neural Network (CNN) and Alexnet for fruit recognition. Automatic fruit recognition can minimize human intervention in their fruit harvesting operations, operation time and harvesting cost. On the other hand, this task is very challenging because of the similarities in shapes, colours and textures among various types of fruits. Thus, a robust technique that can produce good result is necessary. Due to the outstanding performance of deep learning like CNN and its pre-trained models like AlexNet in image recognition, this paper investigates the accuracy of conventional CNN, and Alexnet in recognizing thirty different types of fruits from a publicly available dataset. Besides that, the recognition performance of BoF is also examined since it is one of the machine learning techniques that achieves good result in object recognition. The experimental results indicate that all of these three techniques produce excellent recognition accuracy. Furthermore, conventional CNN achieves the fastest recognition result compared to BoF, and Alexnet.
Melting pots and hotspots: genetic variation within Acanthodactylus erythrurus (Reptilia: Lacertidae) from the Iberian Peninsula

Identification of high levels of intraspecific genetic variability is common among assessments of reptiles from the Iberian Peninsula, conforming to the “refugia within refugia” hypothesis. Divergent genetic lineages are often found to be allopatric, or with limited contact or hybrid zones; such zones are more widely reported in Northern Europe, leading to the “melting pots not hotspots” hypothesis. However, population level sampling is needed to determine if divergent lineages overlap, something that is often missing in phylogenetic studies. Mitochondrial genetic diversity was assessed within the lacertid lizard Acanthodactylus erythrurus across the Iberian Peninsula. Not only were highly divergent lineages recovered in the southern region, but also considerable admixture of these was identified, particularly in northern populations. This has implications for biogeographic scenarios, with patterns typically identified at a larger scale emerging within a single European southern refugium. It also indicates that divergent mtDNA lineages appear to freely mix, at least within this species, which has taxonomic implications.
An Investigation on the performance Of an imidazoline based commercial Corrosion inhibitor on CO2 corrosion Of gas-well tubing steel by EIS technique

The performance of an Imidazoline based commercial corrosion inhibitor in CO2 corrosion of a gas-well tubing steel was studied by employing Electrochemical Impedance Spectroscopy (EIS) technique. Inhibitor performance was investigated by means of its efficiency at various concentration and also its behavior at various exposure time. EIS results showed that inhibitor interaction to the electrode surface obeys Lungmuir adsorption isotherm. Interpretation of some parameters such as Rct, Rpf, Cdl, and Cpf associated to the equivalent circuit fitted to the experimental rsults showed that not only inhibitor efficiency and surface coverage improve by increasing in inhibitor concentration in the solution but also at constant inhibitor concentration both surface coverage and efficiency improve with exposure time and reach to their highest value after 4 hours.
A reduced-peak equivalence for queues with a mixture of light-tailed and heavy-tailed input flows

We determine the exact large-buffer asymptotics for a mixture of light-tailed and heavy-tailed input flows. Earlier studies have found a ‘reduced-load equivalence’ in situations where the peak rate of the heavy-tailed flows plus the mean rate of the light-tailed flows is larger than the service rate. In that case, the workload is asymptotically equivalent to that in a reduced system, which consists of a certain ‘dominant’ subset of the heavy-tailed flows, with the service rate reduced by the mean rate of all other flows. In the present paper, we focus on the opposite case where the peak rate of the heavy-tailed flows plus the mean rate of the light-tailed flows is smaller than the service rate. Under mild assumptions, we prove that the workload distribution is asymptotically equivalent to that in a somewhat ‘dual’ reduced system, multiplied by a certain prefactor. The reduced system now consists of only the light-tailed flows, with the service rate reduced by the peak rate of the heavy-tailed flows. The prefactor represents the probability that the heavy-tailed flows have sent at their peak rate for more than a certain amount of time, which may be interpreted as the ‘time to overflow’ for the light-tailed flows in the reduced system. The results provide crucial insight into the typical overflow scenario.
Measurements of isospin asymmetry and difference of directCPasymmetries in inclusiveB→Xsγdecays

We report measurements of isospin asymmetry $\Delta_{0-}$ and difference of direct $CP$ asymmetries $\Delta A_{CP}$ between charged and neutral $B \to X_s \gamma$ decays. This analysis is based on the data sample containing $772 \times 10^6 B\bar{B}$ pairs that was collected with the Belle detector at the KEKB energy-asymmetric $e^+ e^-$ collider. Using a sum-of-exclusive technique with invariant $X_s$ mass up to 2.8~GeV/$c^2$, we obtain $\Delta_{0-} = \bigl[-0.48 \pm 1.49 {\rm (stat.)} \pm 0.97 {\rm (syst.)} \pm 1.15 {(f_{+-}/f_{00})}\bigr]$\% and $\Delta A_{CP} = \bigl[+3.69 \pm 2.65 {\rm (stat.)} \pm 0.76{\rm (syst.)}\bigr]$\%, where the last uncertainty for $\Delta_{0-}$ is due to the uncertainty on the production ratio of $B^+B^-$ to $B^0\bar{B}^0$ in $\Upsilon(4S)$ decays. The measured value of $\Delta_{0-}$ is consistent with zero, allowing us to constrain the resolved photon contribution in the $B \to X_s \gamma$, and improve the branching fraction prediction. The result for $\Delta A_{CP}$ is consistent with the prediction of the SM. We also measure the direct $CP$ asymmetries for charged and neutral $B \to X_s \gamma$ decays. All the measurements are the most precise to date.
Professionalism in mountain tourism and the claims to professional status of the International Mountain Leader

Mountain Guides and International Mountain Leaders (IMLs) have achieved cross-border recognition of their professional awards. This allows them to work internationally and provides a rare example of an established, state-sanctioned and respected professional group operating within the tourism industry. As it grows, this industry is increasingly looking to elements of professionalism to provide education and training programmes with the status and credibility that can sustain both industry development and public confidence. The case for professionalism amongst IMLs is examined through an in-depth study of the French and British award schemes. Despite their very different origins, histories and cultures, both schemes train and assess candidates for the IML award and have been selected here because they are the largest and oldest of their kind. This comparative study's focus on the structural elements of these two schemes allows certain aspects of the IML's claim to professional status to be evaluated. First, a framework outlining the defining features of professionalism is explicated. This framework is then used as an analytical tool to evaluate the degree to which the French and British IML schemes can be considered professional. This study concludes that the international accreditation of standards within the field of Mountain Leading, together with the monopolisation of key practices and bodies of knowledge, have contributed to the professionalisation of this area of tourism. There remains much scope, however, for the profession to develop effective and meaningful deontological codes and disciplinary procedures that can further uphold professional standards.
The Revolution Revolution: Magnetic Morphology Driven Spin-down

Observations of young open clusters (OCs) show a bimodal distribution of rotation periods that has been difficult to explain with existing stellar spin-down models. Detailed magnetohydrodynamic (MHD) stellar wind simulations have demonstrated that surface magnetic field morphology has a strong influence on wind-driven angular momentum loss. Observations suggest that faster rotating stars store a larger fraction of their magnetic flux in higher-order multipolar components of the magnetic field. In this work, we present an entirely predictive new model for stellar spin-down that accounts for the stellar surface magnetic field configuration. We show how a magnetic complexity that evolves from complex toward simple configurations as a star spins down can explain the salient features of stellar rotation evolution, including the bimodal distribution of both slow and fast rotators seen in young OCs.
Revised petrology and new chronological data on the peralkaline felsic lavas of Ngaoundéré volcanism ( Adamawa plateau , Cameroon , Central Africa ) : evidence of open-system magmatic processes

The petrology of the peralkaline felsic lavas from the Ngaoundéré region was re-examined, together with new chronological data obtained on them, in order to determine their petrogenesis and investigate their peralkaline features. The results showed that all lavas have a microlitic porphyritic texture. They are composed of more than 70% phenocrysts and microlites of alkali feldspar, with diopside, hedembergite, augite, aegirine-augite for trachytes, and nosean, nepheline, kaersutite, titanite, apatite and oxides ̧ set in a matrix of the same minerals, in phonolite. All lavas, Miocene in age, are the result of the fractional crystallization processes undergone by the surrounding basaltic lavas. The titanite crystallization phase is responsible for the concave downward appearance of the REE pattern of peralkaline phonolite, as well as the slight depletion of Nb and Ta. AFC modeling using Pan-African basement rock as contaminant was also intended. The genesis of peralkaline trachytes from less-evolved lavas requires a Ma/Mc ratio of 0.1, and a fractionation process (F ≈ 0.9) involving only feldspar so as to comply with the (Sr/Sr) 9Ma values of ≈ 0.710. Additionally, hydrothermal fluid effects are suspected. The peralkalinity of the lavas is the result of a pronounced fractionation of the Al2O3 component by aluminous-enriched phases, in combination with alkaliand volatile-enriched metasomatized fluids, which have acted through the network of Pan-African cracks. Copyright © 2012 Published by Ed. Univ. „Al. I. Cuza” Iași. All rights reserved.
A Bayesian Classifier Learning Algorithm Based on Optimization Model

Naive Bayes classifier is a simple and effective classification method, but its attribute independence assumption makes it unable to express the dependence among attributes and affects its classification performance. In this paper, we summarize the existing improved algorithms and propose a Bayesian classifier learning algorithm based on optimization model (BC-OM). BC-OM uses the chi-squared statistic to estimate the dependence coefficients among attributes, with which it constructs the objective function as an overall measure of the dependence for a classifier structure. Therefore, a problem of searching for an optimal classifier can be turned into finding the maximum value of the objective function in feasible fields. In addition, we have proved the existence and uniqueness of the numerical solution. BC-OM offers a new opinion for the research of extended Bayesian classifier. Theoretical and experimental results show that the new algorithm is correct and effective.
Exploring Molecular Complexity with ALMA (EMoCA): Deuterated complex organic molecules in Sagittarius B2(N2)

Deuteration is a powerful tracer of the history of the cold prestellar phase in star forming regions. Apart from methanol, little is known about deuterium fractionation of complex organic molecules in the interstellar medium, especially in high mass star forming regions. We use a spectral line survey performed with ALMA to search for deuterated complex organic molecules toward the hot molecular core Sgr B2(N2). Population diagrams and integrated intensity maps are constructed to fit rotational temperatures and emission sizes for each molecule. Column densities are derived by modelling the full spectrum under the LTE assumption. The results are compared to predictions of two astrochemical models that treat the deuteration process. We report the detection of CH2DCN toward Sgr B2(N2) with a deuteration level of 0.4%, and tentative detections of CH2DOH, CH2DCH2CN, the chiral molecule CH3CHDCN, and DC3N with levels in the range 0.05%-0.12%. A stringent deuteration upper limit is obtained for CH3OD (<0.07%). Upper limits in the range 0.5-1.8% are derived for the three deuterated isotopologues of vinyl cyanide, the four deuterated species of ethanol, and CH2DOCHO. Ethyl cyanide is less deuterated than methyl cyanide by at least a factor five. Except for methyl cyanide, the measured deuteration levels lie at least a factor four below the predictions of current astrochemical models. The deuteration levels in Sgr B2(N2) are also lower than in Orion KL by a factor of a few up to a factor ten. The discrepancy between the deuteration levels of Sgr B2(N2) and the predictions of chemical models, and the difference between Sgr B2(N2) and Orion KL may both be due to the higher kinetic temperatures that characterize the Galactic Center region compared to nearby clouds. Alternatively, they may result from a lower overall abundance of deuterium itself in the Galactic Center region by up to a factor ten.
Sharp tunable and additional noise-free optical filter based on Brillouin losses

In this paper, we propose an additional noise-free, independent center frequency and bandwidth tunable optical filter based on stimulated Brillouin scattering (SBS) losses. By suppressing the out-of-band signal with two broadened symmetric SBS losses, tunable pass bandwidths from 500 MHz to 9.5 GHz and the independent center frequency tunability are demonstrated. Considering the limited SBS interaction in the center frequency range, a flat-top response with minimum 0.3 dB ripple is achieved. Assisted by the extra suppression from polarization pulling, a maximum selectivity of 20 dB and an ultrahigh 250 dB/GHz roll-off are reached. A gain-based SBS filter adds noise to the filtered signal. However, for our proposed filter setup, no additional noise is detected due to the transparency in the passband. Considering the wide independent bandwidth and center frequency tunability, flat-top response, and low-noise characteristic, our proposed filter can be perfectly used as a supplement of most commercialized conventional tunable optical single bandpass filters, whose minimum bandwidth is limited by 10 GHz.