Miracle-dz/UniFAR-FTUs huggingface dataset:
Modeling of electron fluxes in the Enceladus plume

[1] Observations by instruments onboard the Cassini spacecraft of Saturn's icy satellite Enceladus have shown that a plume containing water vapor and ice grains is present in the southern hemisphere. Energy distributions of electrons in this plume were measured by the electron sensor part of the Cassini plasma spectrometer (CAPS – ELS). A significant suprathermal electron population was detected. The nature of the electron population is important for understanding the composition and chemistry of the plume plasma because the electron-ion recombination rate depends on the energy distribution and because ionizing collisions by energetic electrons creates new plasma. We present the results of a two-stream electron transport model for plume electrons that includes neutral densities that agree with Cassini Ion and Neutral Mass Spectrometer (INMS) data. Electron production within the plume due to photoionization by solar radiation and by electron impact ionization was included, as were energy losses due to electron-neutral collisions. Model cases were considered that both included and did not include electron inputs from outside the plume. Comparisons are made of model fluxes with measured fluxes by CAPS – ELS on October 9, 2008. The model-data comparisons indicate that photoelectrons (10 eV–70 eV energies) locally produced within the plume can explain the data. The possible role of electron-grain collisions was also explored and it was determined that nanograin densities in excess of 106 cm−3 would be needed to affect the electron distribution.
Route to achieving enhanced quantum capacitance in functionalized graphene based supercapacitor electrodes

We have investigated the quantum capacitance () in functionalized graphene modified with ad-atoms from different groups in the periodic table. Changes in the electronic band structure of graphene upon functionalization and subsequently the of the modified graphene were systematically analyzed using density functional theory (DFT) calculations. We observed that the can be enhanced significantly by means of controlled doping of N, Cl and P ad-atoms in the pristine graphene surface. These ad-atoms are behaving as magnetic impurities in the system, generating a localized density of states near the Fermi energy which, in turn, increases charge (electron/hole) carrier density in the system. As a result, a very high quantum capacitance was observed. Finally, the temperature dependent study of for Cl and N functionalized graphene shows that the remains very high in a wide range of temperatures near room temperature.
Characteristics of Korean Soybean Paste ( Doenjang) Prepared by the Fermentation of Black Soybeans

The changes in components and biological activities of doenjang samples prepared with black soybeans and fermented with Bacillus subtilis SCB were investigated. The amino nitrogen (A-N) contents of samples increased with increasing black soybean content. A doenjang product made using a 1:1 ratio of soybeans-black soybeans showed a maximum level of genistein and daidzein isoflavones (1111.6 ㎍/g) at 110 days of fermentation, along with decreasing contents of genistin and daidzin due to the conversion to aglycones. The black soybean-only doenjang sample showed higher protease activity, including caseinolytic and fibrinolytic enzyme activities, than the other samples, and had relatively higher polyphenol content and DPPH radical scavenging activity. Therefore, doenjang made with additions of black soybeans and fermented by B. subtilis SCB may have improved physiological properties, suggesting this to be a valuable method of preparation.
A Precision Measurement of the Mass of the Black Hole in NGC 3258 from High-resolution ALMA Observations of Its Circumnuclear Disk

We present ∼0. ″10 resolution Atacama Large Millimeter/submillimeter Array (ALMA) CO(2−1) imaging of the arcsecond-scale (r ≈ 150 pc) dusty molecular disk in the giant elliptical galaxy NGC 3258. The data provide unprecedented resolution of the cold gas disk kinematics within the dynamical sphere of influence of a supermassive black hole (BH), revealing a quasi-Keplerian central increase in projected rotation speed rising from 280 km s−1 at the disk’s outer edge to >400 km s−1 near the disk center. We construct dynamical models for the rotating disk and fit beam-smeared model CO line profiles directly to the ALMA data cube. Our models incorporate both flat and tilted-ring disks that provide a better fit of the mildly warped structure in NGC 3258. We show that the exceptional angular resolution of the ALMA data makes it possible to infer the host galaxy’s mass profile within r = 150 pc solely from the ALMA CO kinematics, without relying on optical or near-infrared imaging data to determine the stellar mass profile. Our model therefore circumvents any uncertainty in the BH mass that would result from the substantial dust extinction in the galaxy’s central region. The best model fit yields , with a statistical model-fitting uncertainty of just 0.18% and systematic uncertainties of 0.62% from various aspects of the model construction and 12% from uncertainty in the distance to NGC 3258. This observation demonstrates the full potential of ALMA for carrying out highly precise measurements of in early-type galaxies containing circumnuclear gas disks.
Surface characteristics and taxonomy of brewing yeasts

The article is dealing with taxonomy of brewing yeasts, methods their classification and identification; hybrid character of brewing yeasts is highlighted with related problems in their classification. The methods of molecular biology are mostly used for the classification of brewing yeasts, where the differences in chromosomal and mitochondrial DNA are monitored–genotypic methods. Polyphasic taxonomy of yeasts is based on combination genotypic, phenotypic and chemotaxonomic methods. Important quality of brewing yeasts are surface characteristic, which could strongly affect yeast flocculation. The terms „flocculation“ and „hydrophobicity“ are clarified, factors affecting flocculation are described, and the methods of polyphasic approach in brewing yeast taxonomy are summarized.
Syndrome of professional burn out in home service for elderly

Aim: The aim of this study was to examine if the staff of the “home service” was in a burnout situation and which is their attitude to their job. Methodology: In order to conduct the study workers from 36 municipalities of the Prefecture of Attica were selected which enumerated to a population of 123 workers. This staff included social workers, nurses, assistants’ nurses and familial assistants. As tool for the research the Maslach Burnout Inventory (MBI) was used. The study protocol for linking anonymized staff data and optional sample participation was approved by the institutional review board of the municipalities. Data analysis was performed using STATA statistical package. Statistical analysis of Pearson cross-correlations test was used where p<. 05 was considered statistically significant in all analyses. Results:The results showed that the staff does not experience high levels of Professional burnout syndrome in the present time as the indicating values were low in the factor of Emotional Exhaustion (EE) 63.22%, moderate in the factor of Depersonalization (D) 47.13%, and moderate (37.93%) and high (37.93%) in the factor of Personal Accomplishment (PA). According to Pearson cross-correlations test, P.A. is related positively with the level of education (p=0.01), the fix by fate professional choice (p=0.05) and the percentage of weekly visits in elderly houses (p=0.000). Interest causes the negative cross-correlation of years of work in the service (p=0.34) with Personal Accomplishments. Moreover, the factor of depersonalization had positive crosscorrelation with their total years of work. Conclusion : The results showed that the staff did not experience Syndrome of Professional burnout, but the factor of Depersonalization was found already solidified and that has positive cross-correlation with their total years of work; those points out future risk for the staff working in the "Help in the Home" service.
The Energetics and Tidally Induced Reverse Renewal in a Two-Silled Fjord

A laterally integrated, two-dimensional numerical model is used to examine the influence of the M2 tide on the circulation in the Saguenay Fjord, a two-silled fjord (with a ‘‘large’’ inner and a ‘‘small’’ outer basin) located on the north shore of the St. Lawrence Estuary. It is found that the M2 tide is more vigorous in the outer than in the inner basin and that more vertical mixing occurs in the outer basin. Therefore, the density at depth in the outer basin decreases faster than it does in the inner basin, and the resulting horizontal pressure gradient causes a bottom flow of water from the inner to the outer basin across the inner sill. This ‘‘reverse renewal’’ is evident in both the available observations and the simulation. According to the model, much of the M2 energy withdrawn from the surface tide is fed into the internal tide. Significant tidal energy is also advected by the mean flow velocity. Approximately 25% of the net energy flux into the fjord is dissipated within 2 km of the outer sill. Because of the baroclinic pressure (i.e., the total pressure but with the influence of the surface displacement removed) the subtidal circulation is associated with very large energy fluxes within the fjord. These fluxes are much larger than the net rate at which tidal energy enters the fjord and they are greater than the subtidal, advective energy flux. They represent a large redistribution of energy within the fjord and their horizontal divergence along the fjord is almost in balance with the time rate of change of potential energy. When a flux Richardson number is calculated for the inner basin below sill depth, a value of 0.075 is obtained, which is close to values found for other fjords.
REQUIREMENTS AND DEVELOPMENT OF A COMPUTERIZED APPROACH FOR ANALYZING FUNCTIONAL RELATIONSHIPS AMONG HVAC COMPONENTS USING BUILDING INFORMATION MODELS

Heating, ventilating and air conditioning (HVAC) systems account for about 40% of the energy consumed in buildings. They directly control the indoor air quality and determine occupant comfort. Therefore, correct operation of HVAC systems is critical for ensuring the normal functions of the buildings. Due to the continued increase in their complexity, manual operation and maintenance of the HVAC systems has become more and more difficult. Computerized approaches, such as Fault detection and diagnosis and automated commissioning approaches, have been proposed to automate this process. These approaches use data from the HVAC systems and building context and provide information about the performance of the systems to the operator. However, the existing information standards, such as Industry Foundation Classes (IFC) and AEX cfiXML, mainly represent the geometric information and categories of the HVAC components. One important type of information that is missing is the functional relationships of the HVAC components. Functional relationships represent how different HVAC components work together to serve the functions of the system. For example, a sensor that monitors the temperature of a space is functionally related to the Variable Air Volume (VAV) box that controls the temperature of the same space. Therefore, functional relationships are needed by the HVAC system operator to reason about and adjust their configuration. The objective of the presented work is to develop a computerized approach that can automatically analyse the functional relationships of HVAC components using the available information from the existing Building Information Models (BIM). This includes the exploration of needed functional relationships of HVAC components, the classifications of functionalities of HVAC equipment and components, the development of a functional taxonomy of HVAC components, and the implementation of a prototype system for analysing the functional relationships. The primary result of the presented work is the development of an extensible computerized approach that can automatically reason about the functional relationships of typical HVAC components using information from BIM.
Combining mathematical forecasting with intuitive techniques for better decision making

Mathematical models are used to forecast new product sales. Forecasting using mathematical methods have been criticized by many researchers, as the forecasts are often not sufficiently accurate to be applied to business decisions. Forecasting new product sales may be improved by using intuitive techniques. In this paper intuitive techniques are applied to mathematical forecasting models. A growth curve predication model is developed; in addition a reference data set is used to validate the outputs, providing important lessons for managers.
Measuring Loss and Reordering with Few Bits

This work proposes a method for explicit passive measurability of packet loss and reordering we call the known sequence. The known sequence method adds few bits (symbols) taken from a deterministic, high-entropy sequence to each packet. On-path observers who are able to generate the sequence can synchronize on it and infer errors when an unexpected symbol arrives. Loss and reordering rates obtained from the known sequence can be used for monitoring and troubleshooting. O↵sets of inferred losses can be used to determine if the loss pattern is independent. We propose a method to improve the practical utility of XOR-based forward error correction based on the loss pattern. In addition, we map out a vision for a next-generation metrics API for SCION.
Microsoft AI Challenge India 2018: Learning to Rank Passages for Web Question Answering with Deep Attention Networks

This paper describes our system for The Microsoft AI Challenge India 2018: Ranking Passages for Web Question Answering. The system uses the biLSTM network with co-attention mechanism between query and passage representations. Additionally, we use self attention on embeddings to increase the lexical coverage by allowing the system to take union over different embeddings. We also incorporate hand-crafted features to improve the system performance. Our system achieved a Mean Reciprocal Rank (MRR) of 0.67 on eval-1 dataset.
Predicting Student Academic Performance in KSA using Data Mining Techniques

The main objective of higher education institutions is to provide quality education to its students. One way to achieve highest level of quality is to identify factors affecting academic performance and then trying to resolve weakness of these factors. The specific objective of the proposed research work is to find out if there are any patterns in the available data (student and courses records) that could be useful for predicting students’ performance. The study involved a sample of 150 students collected from Najran University students in Saudi Arabia. The data was captured and arranged with the use of statistical package for social sciences (SPSS) and data mining tool (clementine). Developing an accurate student’s performance prediction model is challenging task. Data mining based model were used to identify which of the known factors can give an early indicator of expected performance. This paper employs both feature reduction and classification technique to reduce error rate. The experimental results reveal significant relationships between including both practical work and assignments in course and its success rate. But, on the other hand the number of given assignment has a negative impact on course academic performance. In context of factors affect student academic performance, the most affecting factor is student attendance in class in addition to final exam and mid exam grades.
A Novel Software-Defined Networking Controller: the Distributed Active Information Model (DAIM)

This paper presents a new OpenFlow controller: the Distributed Active Information Model (DAIM). The DAIM controller was developed to explore the viability of a logically distributed control plane. It is implemented in a distributed way throughout a software-defined network, at the level of the switches. The method enables local process flows, by way of local packet switching, to be controlled by the distributed DAIM controller (as opposed to a centralised OpenFlow controller). The DAIM ecosystem is discussed with some sample code, together with flowcharts of the implemented algorithms. We present implementation details, a testing methodology, and an experimental evaluation. A performance analysis was conducted using the Cbench open benchmarking tool. Comparisons were drawn with respect to throughput and latency. It is concluded that the DAIM controller can handle a high throughput, while keeping the latency relatively low. We believe the results to date are potentially very interesting, especially in light of the fact that a key feature of the DAIM controller is that it is designed to enable the future development of autonomous local flow process and management strategies.
Cardio Online Reader â Conjunctions in Cardiology Knowledge

Background: The progress of scientific knowledge produces an excessive amount of scholarly literature. For effective clinical use it is necessary to use time, quality and relevance filtering. Objectives: We decided to create an independent web based interface for searching the PubMed Database for recent evidence-based articles in the domain of cardiology. Results: The Cardio Online Reader (COR) application (http://neo.euromise.cz/cor) offers an easy way to reach valid and relevant articles filtered by keywords, MeSH terms, authors, date of publication and type of publication. Results can be commented, rated, stored as citations and shared using most popular web sharing services. Conclusion: Using COR can positively affect clinical decisions of physicians bringing them relevant and up-to-date scientific information.
Functional and genetic profiling tools: insight to the black box of vermicomposting process.

The process of vermicomposting is highly dynamic, as it involves a complex interaction of earthworms with diverse microbial species. Over the last two decades, the focus of research has been mainly on the conversion of various types of organic wastes and pollutants such as agricultural, municipal and industrial wastes into vermicompost and on the development of parameters to assess maturity. There is however a lack of knowledge on the process dynamics and the complex interactions that occur between the microbes and earthworms during vermicomposting. A plethora of techniques such as biomass measurement, respiration rate, and enzyme activities are in routine use for assessment of vermicomposting dynamics at process level. However, less attention has been paid to the techniques useful in revealing community-level changes, which can give a significant insight into the microbe-earthworm interactions that finally affects the quality of vermicompost. Methods to study community-level changes such as community-level physiological profiling (CLPP), phospholipid fatty acid analysis (PLFA) and genetic fingerprinting have been commonly used in research on microbial ecology of soil, sediments, gut, and aerobic and anaerobic reactors, but not applied widely in vermicomposting ecosystems. In this review, we discuss the inventory of techniques relevant to vermicomposting process and which can provide significant knowledge on organic matter transformations and community-level changes. Furthermore, this review also brings to light the role of multivariate statistical analysis in predicting the possible relationship between the process-level and the community-level changes. A polyphasic approach to vermicomposting research is thus suggested which will facilitate in opening the blackbox of this complex and dynamic process. _____________________________________________________________________________________________________________
Monodominance in the ectomycorrhizal Dicymbe corymbosa (Caesalpiniaceae) from Guyana

Dominance of primary rain forests by the ectomycorrhizal, leguminous canopy tree Dicymbe corymbosa (Caesalpiniaceae) was investigated in the Pakaraima Mountains of western Guyana. In five 1-ha forest inventory plots in the Upper Ireng and Upper Potaro River drainages basal areas of D. corymbosa ranged from 38.4-52.8 m2 ha-1 (63-85% of total) among all trees ≥10 cm diameter at breast height (dbh), values in the upper range for tropical moist forests worldwide. The high basal areas for D. corymbosa were due to the prevalence of large (>150 cm dbh), multi-stemmed individuals. Stem densities in Dicymbe plots ranged from 276-433 ha-1, with D. corymbosa contributing 24.6-59.8%. In three 1-ha mixed forest plots adjacent to the Dicymbe plots, D. corymbosa was absent. In the mixed forests, stem densities were higher (480-585 ha-1), basal areas were lower (36.7-39.8 m2 ha-1), species diversity was higher, and canopy tree species were more equitably distributed than in the Dicymbe plots. Tree community composition was not qualitatively different between Dicymbe and mixed forests. In the Dicymbe plots, mean sapling and seedling densities of D. corymbosa were significantly higher than most other canopy species, indicating persistent monodominance. Edaphic variation did not account for variation in forest composition. Life history traits are discussed which may contribute to clumping in D. corymbosa, including coppicing and mast-fruiting, and the potential role of litter-trapping physiognomy and ectomycorrhiza-mediated nutrient dynamics in promoting monodominance is noted.
Bounds and Bunching: Distributions of Air Pollutants Produced by New Automobiles

Euro norms set limits on per-kilometer emissions of air pollutants produced by new cars. Satisfying these limits is always costly, the existing models generally assume that cars are produced as to just satisfy the norms. This theory predicts bunching of measured emissions below the limits. We find this not to be consistent with the data. In fact, medians of measured emissions are often at around one half or less of the respective limit and are supported by wide distributions. Implications for optimum tax policies are briefly discussed.
TANGO I: ISM in nearby radio galaxies. Molecular gas

Powerful radio-AGN are hosted by massive elliptical galaxies which are usually very poor in molecular gas. Nevertheless gas is needed in the very center to feed the nuclear activity. We aim to study the molecular gas properties (mass, kinematics, distribution, origin) in such objects, and to compare them with results of other known samples. We have performed at the IRAM-30m telescope a survey of the CO(1-0) and CO(2-1) emission in the most powerful radio galaxies of the Local Universe, selected only on the basis of their radio continuum fluxes. The main result of our survey is the very low content in molecular gas of such galaxies compared to spiral or FIR-selected galaxies. The median value of the molecular gas mass, including detections and upper limits, is 2.2x10^8 Msun. If separated into FR-I and FR-II types, a difference in H_2 masses between them is found. The median value of FR-I galaxies is about 1.9x10^8 and higher for FR-II galaxies, about 4.5x10^8 Msun but this is very probably entirely due to a Malmquist bias. Our results contrast with previous surveys, mainly selected through the FIR emission, implying larger observed masses of molecular gas. Moreover, the shape of CO spectra suggest the presence of a central molecular gas disk in 30% of these radio galaxies, a lower rate than in other active galaxy samples.