Miracle-dz/UniFAR-FTUs huggingface dataset:
The Effect of a Current Free Double Layer Below the Photosphere on the Acceleration of the Solar Wind

Neither the collisional hydrodynamic nor the collisionless kinetic models have yet been able to fully explain the acceleration of the fast solar wind without ad hoc assumptions of additional energy input or suprathermal electron populations at the base of the models in the lower corona. Separate research has shown that plasma naturally forms a Current Free Double Layer when expanding into a lower-density region, the effect of which is to generate a suprathermal electron population and beams of fast ions on the low potential side. It is suggested that the expansion of the dense plasma in the body of the Sun will form a stationary Current Free Double Layer below the photosphere and thus provide initial ion acceleration together with the type of electron velocity distribution function that kinetic models require as boundary conditions. The turbulence generated by the outflowing particle beams colliding with the low-density plasma in and above the upper chromosphere may contribute to the additional wave energy which the hydrodynamic models require. The implications of the present model for the coronal heating problem are also explored.
Speed dependent stochasticity capacitates Newell model for synchronized flow and oscillation growth pattern

This paper has incorporated the stochasticity into the Newell car following model. Three stochastic driving factors have been considered: (i) Driver's acceleration is bounded. (ii) Driver's deceleration includes stochastic component, which is depicted by a deceleration with the randomization probability that is assumed to increase with the speed. (iii) Vehicles in the jam state have a larger randomization probability. Two simulation scenarios are conducted to test the model. In the first scenario, traffic flow on a circular road is investigated. In the second scenario, empirical traffic flow patterns in the NGSIM data induced by a rubberneck bottleneck is studied, and the simulated traffic oscillations and synchronized traffic flow are consistent with the empirical patterns. Moreover, two experiments of model calibration and validation are conducted. The first is to calibrate and validate using experimental data, which illustrates that the concave growth pattern has been quantitatively simulated. The second is to calibrate and cross validate vehicles' trajectories using NGSIM data, which exhibits that the car following behaviors of single vehicles can be well described. Therefore, our study highlights the importance of speed dependent stochasticity in traffic flow modeling, which cannot be ignored as in most car-following studies.
Helping Students to Write Better through Reading and Writing Connections Strategy

One of the causes of students’ difficulties in writing is related to the lack of knowledge on how to write. This might be caused by the lack of awareness that a piece of writing might have its own pattern or organization of ideas depending on the topic. Therefore, students need to be exposed with different kinds readings materials in order to develop their awareness on how writing is developed into differrent kinds of patterns of ideas. This study is intended to help students improve their writing achievement especially in writing an essay by integrating the reading and writing activitivities. The students involved in an integrated reading and writing activity in order to help the students develop their writing skills. This study involved 16 students of English Education Study Program who took the writing 3 course. Therefore, convinient sampling method is applied. The results of this study showed that there was an improvement in the students’ writing achievement in means from 63.3 in pretest to 79.8 in the post test. The results of the paired-sample t-test also confirmed that there is a significant difference in students’ essay writing achievement before and after they were taught by using reading and writing connections strategy. Organization of ideas, focus and detail, and voice are the aspects which were mostly developed after the treatment. Therefore, it can be concluded that reading and writing connections strategy is effective in improving students’ essay writing achievement.
Use of Recurrent ANN and Hybrid EA for the Prediction of Phytoplankton Abundance and Succession Before and After Eutrophication Control of Two Shallow Lakes

Eleven years of water quality time-series of the two Dutch lakes Veluwemeer and Wolderwijd were subject to predictive modelling by recurrent supervised artificial neural networks (RNN) and hybrid evolutionary algorithms (HEA). The modeling aimed at forecasting changes of the phytoplankton community in response to the control of external nutrient loadings and fish abundances as consecutively implemented to both lakes since 1979. The water quality time-series of both lakes were structured for the RNN and HEA modeling in order to reflect following three different management periods by both training and validation datasets: no management (19761978), lake flushing and waste water treatment (1979 onwards) and lake flushing, waste water treatment and food web manipulation (19911993). This approach facilitated a comparative analysis for the two lakes and the three management periods. Firstly recurrent RNN achieved reasonably accurate results for 5-daysahead forecasting of abundances of blue-green algae Oscillatoria and green algae Scenedesmus in both lakes. Secondly hybrid evolutionary algorithms (HEA) achieved similar good forecasting results but also provided model representations for both algae species in the form of rule sets. HEA has been designed to evolve both the structure of rule sets as well as the parameter values imbedded in the rule sets by means of a genetic algorithms. With regards to the different approaches for eutrophication management the modeling results have shown that only the combination of external nutrient control with food web manipulation has changed the lakes from hypereutrophic to mesotrophic conditions reflected by the change from the dominance of blue-green algae Oscillatoria to the dominance of green algae Scenedesmus. Even though both modeling techniques have forecasted the succession of two functional algal groups represented by Oscillatoria and Scenedesmus only HEA provides rule sets for the explanation of these ecological changes. The results revealed that phosphorus limitation by means of seasonal lake flushing and wastewater treatment in combination with increased zooplankton grazing by food-web manipulation diminished the abundance of the harmful Oscillatoria but enhanced the abundance of harmless Scenedesmus. These findings consent well with literature findings e.g. by Benndorf (1995) that the eutrophic lakes requires primarily efficient nutrient control that secondarily can be finetuned by food-web manipulation.
Learning a Driving Simulator

this http URL's approach to Artificial Intelligence for self-driving cars is based on an agent that learns to clone driver behaviors and plans maneuvers by simulating future events in the road. This paper illustrates one of our research approaches for driving simulation. One where we learn to simulate. Here we investigate variational autoencoders with classical and learned cost functions using generative adversarial networks for embedding road frames. Afterwards, we learn a transition model in the embedded space using action conditioned Recurrent Neural Networks. We show that our approach can keep predicting realistic looking video for several frames despite the transition model being optimized without a cost function in the pixel space.
A Consistent Estimator of the Evolutionary Rate

We consider a branching particle system where particles reproduce according to the pure birth Yule process with the birth rate λ, conditioned on the observed number of particles to be equal n. Particles are assumed to move independently on the real line according to the Brownian motion with the local variance σ2. In this paper we treat n particles as a sample of related species. The spatial Brownian motion of a particle describes the development of a trait value of interest (e.g. log-body-size). We propose an unbiased estimator of the evolutionary rate ρ2 =σ2/λ. The estimator is proportional to the sample variance computed from n trait values. We find an approximate formula for the standard error of based on a neat asymptotic relation for the variance of .
Influence of Biopsychosocial Factors on the Survival of the Elderly in Northeast Brazil—A Prospective Study

Background. Identifying the risk factors peculiar to each population has a great relevance, because it enables health policy formulators to analyze information accurately and by doing so, define objectives and action programs aimed at a qualitative and economically feasible solution to the problem. Thus, this study aimed at identifying the risk factors for survival in elderly in a city in the state of Rio Grande do Norte (RN), Brazil. Methods. A prospective study was carried out, where 310 elderly persons were selected to form a baseline. The follow-up was 53 months. The predictive variables were divided into sociodemographic, physical health, neuropsychiatric and functional capacity. Statistical analysis was performed using bivariate analysis, survival analysis, followed by Cox regression in the multivariate analysis. Results. A total of 60 (19.3%) elderly individuals died during the follow-up. The survival mean was 24.8 months. In the Cox analysis, dependence in basic activities of daily living (HR = 3.55), cognitive deficit (HR = 4.22) and stroke (HR = 3.35) continued as independent risk factors for death. Discussion. The risk factors found in the study can be interpreted as the primary predictors for death among elderly members of the community.
Air Pollution and Symptoms of Depression in Elderly Adults

Background: Although the effect of air pollution on various diseases has been extensively investigated, few studies have examined its effect on depression. Objectives: We investigated the effect of air pollution on symptoms of depression in an elderly population. Methods: We enrolled 537 participants in the study who regularly visited a community center for the elderly located in Seoul, Korea. The Korean version of the Geriatric Depression Scale-Short Form (SGDS-K) was used to evaluate depressive symptomatology during a 3-year follow-up study. We associated ambient air pollutants with SGDS-K results using generalized estimating equations (GEE). We also conducted a factor analysis with items on the SGDS-K to determine which symptoms were associated with air pollution. Results: SGDS-K scores were positively associated with interquartile range (IQR) increases in the 3-day moving average concentration of particulate matter with an aerodynamic diameter ≤ 10 μm (PM10) [17.0% increase in SGDS-K score, 95% confidence interval (CI): 4.9%, 30.5%], the 0–7 day moving average of nitrogen dioxide [NO2; 32.8% (95% CI: 12.6%, 56.6%)], and the 3-day moving average of ozone [O3; 43.7% (95% CI: 11.5%, 85.2%)]. For these three pollutants, factor analysis showed that air pollution was more strongly associated with emotional symptoms such as feeling happy and satisfied than with somatic or affective symptoms. Conclusions: Our study suggests that increases in PM10, NO2, and O3 may increase depressive symptoms among the elderly. Of the symptoms evaluated, ambient air pollution was most strongly associated with emotional symptoms.
Class numbers of imaginary abelian number fields

Let N be an imaginary abelian number field. We know that h-, the relative class number of N, goes to infinity as fN, the conductor of N, approaches infinity, so that there are only finitely many imaginary abelian number fields with given relative class number. First of all, we have found all imaginary abelian number fields with relative class number one: there are exactly 302 such fields. It is known that there are only finitely many CMfields N with cyclic ideal class groups of 2-power orders such that the complex conjugation is the square of some automorphism of N. Second, we have proved in this paper that there are exactly 48 such fields.
PENYINGKAPAN CITRA PEREMPUAN CERPEN MEDIA INDONESIA: KAJIAN FEMINISME

One of the female phenomena which was authored by the authors short stories in Media Indonesia is the narrative of oppressed women. The purpose of this study is to explore the image of women in short stories in the Media Indonesia. This research is descriptive qualitative research that focuses on the image of women. The approach used in this research is the feminism approach. The data were analysis techniques using heuristic and hermeneutic techniques. The results of the study indicate that there are various negative treatments experienced by women. The author used the short stories as a representation of their images through the Media Indonesia daily. Women's image is manifested in the form of physical image, psychic, helpless, resigned to the situation, housewife, loyalty, child guard, domestic, husband's companion, and social.
THE COMPLEXITY OF FINITE OBJECTS AND THE DEVELOPMENT OF THE CONCEPTS OF INFORMATION AND RANDOMNESS BY MEANS OF THE THEORY OF ALGORITHMS

In 1964 Kolmogorov introduced the concept of the complexity of a finite object (for instance, the words in a certain alphabet). He defined complexity as the minimum number of binary signs containing all the information about a given object that are sufficient for its recovery (decoding). This definition depends essentially on the method of decoding. However, by means of the general theory of algorithms, Kolmogorov was able to give an invariant (universal) definition of complexity. Related concepts were investigated by Solomonoff (U.S.A.) and Markov. Using the concept of complexity, Kolmogorov gave definitions of the quantity of information in finite objects and of the concept of a random sequence (which was then defined more precisely by Martin-Lof). Afterwards, this circle of questions developed rapidly. In particular, an interesting development took place of the ideas of Markov on the application of the concept of complexity to the study of quantitative questions in the theory of algorithms. The present article is a survey of the fundamental results connected with the brief remarks above.
RACTOPAMINE ( addendum ) First draft prepared by Professor

Explanation. 119 Biological data . 121 Biochemical aspects . 121 Absorption, distribution, excretion . 121 Biotransformation. 123 Pharmacokinetics in humans. 124 Comparative pharmacokinetics of b-adrenoceptor agonists . 124 Structural requirements . 124 Absorption, distribution and excretion. 125 Biotransformation. 127 Toxicological studies . 128 Short-term studies of toxicity . 128 Long-term studies of toxicity and carcinogenicity . 130 Genotoxicity . 135 Reproductive toxicity. 140 Special studies. 140 Pharmacodynamic effects: b-adrenergic receptor selectivity for stereoisomers of ractopamine . 140 Cardiovascular effects. 141 Microbiological effects . 147 Observations in humans . 147 Cardiovascular effects . 147 Musculo-skeletal effects . 150 Behavioural changes . 150 Metabolic effects. 150 Tolerance . 151 Bronchial hyperreactivity and increased airway inflammation . 151 Tumorigenicity. 151 Comments . 152 Evaluation . 157 References . 157
Automatic audio content analysis

This paper describes the theoretic framework and applications of automatic audio content analysis. Research in multimedia content analysis has so far concentrated on the video domain. We demonstrate the strength of automatic audio content analysis. We explain the algorithms we use, including analysis of amplitude, frequency and pitch, and simulations of human audio perception. These algorithms serve us as tools for further audio content analysis. We use these tools in applications like the segmentation of audio data streams into logical units for further processing, the analysis of music, as well as the recognition of sounds indicative of violence like shots, explosions and cries.
The Effectiveness of Top Management Groups in Manufacturing Organisations

We test whether demographic characteristics and team processes in top management teams predict the subsequent productivity and profitability of their companies in 42 UK manufacturing organisation. The results that there are independent effects of both demographic characteristics and team processes. Team member mean educational level and team tenure both predict the subsequent productivity and profitability of the companies positively, while age diversity in the team is a negative predictor of company performance. Team processes (clarity of and commitment to objectives, participation, task orientation, and support for innovation) predict (positively) company performance. Only mean educational level, of the demographic variables, also predicts team processes, suggesting that the effects of demographic variables on company performance are not strongly mediated by team processes. The implications of these findings for the composition and development of top management teams are discussed.
Mutualism Breakdown by Amplification of Wolbachia Genes

Most insect species are associated with vertically transmitted endosymbionts. Because of the mode of transmission, the fitness of these symbionts is dependent on the fitness of the hosts. Therefore, these endosymbionts need to control their proliferation in order to minimize their cost for the host. The genetic bases and mechanisms of this regulation remain largely undetermined. The maternally inherited bacteria of the genus Wolbachia are the most common endosymbionts of insects, providing some of them with fitness benefits. In Drosophila melanogaster, Wolbachia wMelPop is a unique virulent variant that proliferates massively in the hosts and shortens their lifespan. The genetic bases of wMelPop virulence are unknown, and their identification would allow a better understanding of how Wolbachia levels are regulated. Here we show that amplification of a region containing eight Wolbachia genes, called Octomom, is responsible for wMelPop virulence. Using Drosophila lines selected for carrying Wolbachia with different Octomom copy numbers, we demonstrate that the number of Octomom copies determines Wolbachia titers and the strength of the lethal phenotype. Octomom amplification is unstable, and reversion of copy number to one reverts all the phenotypes. Our results provide a link between genotype and phenotype in Wolbachia and identify a genomic region regulating Wolbachia proliferation. We also prove that these bacteria can evolve rapidly. Rapid evolution by changes in gene copy number may be common in endosymbionts with a high number of mobile elements and other repeated regions. Understanding wMelPop pathogenicity and variability also allows researchers to better control and predict the outcome of releasing mosquitoes transinfected with this variant to block human vector-borne diseases. Our results show that transition from a mutualist to a pathogen may occur because of a single genomic change in the endosymbiont. This implies that there must be constant selection on endosymbionts to control their densities.
Supervised hashing binary code with deep CNN for image retrieval

Approximate nearest neighbor search is a good method for large-scale image retrieval. We put forward an effective deep learning framework to generate binary hash codes for fast image retrieval after knowing the recent benefits of convolutional neural networks (CNNs). Our concept is that we can learn binary codes by using a hidden layer to present the latent concepts dominating the class labels when the data labels are usable. CNN also can be used to learn image representations. Other supervised methods require pair-wised inputs for binary code learning. However, our method can be used to learn hash codes and image representations in a point-by-point manner so it is suitable for large-scale datasets. Experimental results show that our method is better than several most advanced hashing algorithms on the CIFAR-10 and MNIST datasets. We will further demonstrate its scalability and efficiency on a large-scale dataset with 1 million clothing images.
Personalized routes for mobile tourism

This paper deals with the problem of deriving personalized recommendations for daily sightseeing itineraries for tourists visiting any destination. Our approach considers selected places of interest that a traveler would potentially wish to visit and derives a near-optimal itinerary for each day of visit; the places of potential interest are selected based on stated or implied user preferences. Our method enables the planning of customized daily personalized tourist itineraries considering user preferences, time available for visiting sights in daily basis, opening days of sights and average visiting times for these sights. Herein, we propose a heuristic solution to this problem and discuss its implementation aspects.
ATRX Dysfunction Induces Replication Defects in Primary Mouse Cells

The chromatin remodeling protein ATRX, which targets tandem repetitive DNA, has been shown to be required for expression of the alpha globin genes, for proliferation of a variety of cellular progenitors, for chromosome congression and for the maintenance of telomeres. Mutations in ATRX have recently been identified in tumours which maintain their telomeres by a telomerase independent pathway involving homologous recombination thought to be triggered by DNA damage. It is as yet unknown whether there is a central underlying mechanism associated with ATRX dysfunction which can explain the numerous cellular phenomena observed. There is, however, growing evidence for its role in the replication of various repetitive DNA templates which are thought to have a propensity to form secondary structures. Using a mouse knockout model we demonstrate that ATRX plays a direct role in facilitating DNA replication. Ablation of ATRX alone, although leading to a DNA damage response at telomeres, is not sufficient to trigger the alternative lengthening of telomere pathway in mouse embryonic stem cells.
THE EFFECTS OF INQUIRY-BASED LEARNING AND LEARNING STYLES ON PRIMARY SCHOOL STUDENTS’ CONCEPTUAL UNDERSTANDING IN MULTIMEDIA LEARNING ENVIRONMENT

This research aimed to identify the effects of inquiry-based learning on the conceptual understanding of students with various learning styles in the multimedia learning environment. This research was factorial experiment with the quasi-experimental design. There were total of 157 primary school students in Bali, Indonesia being involved as the subjects of the study. There were two instruments used in this research. The first instrument was a questionnaire adapted from Index of Learning Style (ILS) developed by Felder and Soloman for measuring the verbal-visual learning styles. The second instrument was the conceptual understanding test for measuring students’ conceptual understanding in the form of multiple-choice test. The research discovered three findings as follows: (1) there is a significant difference in terms of conceptual understanding between students who are taught by inquiry-based learning and direct instruction strategy, (2) there is a significant difference in terms of students conceptual understanding between visual and verbal students, (3) there is a significant interaction between different learning strategies (inquiry based learning and direct instruction strategy) and students’ learning styles (visual verbal) toward students conceptual understanding.