Miracle-dz/UniFAR-FTUs huggingface dataset:
Modelling the radio and X-ray emission from T-Tauri flares

T-Tauri stars are known for their high levels of magnetic activity and variability. Both classical and weak-line T-Tauri stars are overluminous in the radio compared with the well-established Güdel-Benz relation between radio and X-ray luminosity for solar and main sequence stellar flares. We show that there is little difference in the observational properties of classical T-Tauri stars and weak-line T-Tauri stars. We then model a typical T-Tauri circumstellar disk system magnetosphere to predict the radio emission from flares associated with the circumstellar disk and accretion events. We assume that energetic electrons are generated in a large-scale magnetic flux tube due to a reconnection event with the accretion disc field at 4R . Our standard model, with a dipolar magnetic field with a strength of 2kG at the stellar surface and non-thermal and thermal densities of 2.5×1011cm−3 and 5.0×1011cm−3 respectively, produces both X-ray and radio emission consistent with observations (logLX=30.5, logLR=16.3). Varying the model parameters we can reproduce the observed range of radio and X-ray emission. The peak radio luminosity and the frequency of this peak (which occurs at >10 GHz and possibly beyond 100 GHz for some sets of parameters) depend on the fraction of non-thermal particles and may be used as a diagnostic of this quantity. The surface field strength was varied from 0.5 to 7kG, with the peak flux increasing by over three orders of magnitude. The models provide a framework for constraining the properties of these sources and to guide and interpret future observations.
Models of Experience in Practice : Frameworks in the Field

The plethora of theories in the field of UX can be highly relevant to practice. This paper discusses the successful use of seven theories in the evaluation of TAPT, an experience-oriented design method. Four models of experience and one discussion of working practice and UX were used for direct evaluation; two other theories drove the methodology of TAPT’s evaluation.
Valuative multiplier ideals

The main goal of this paper is to construct an algebraic analogue of quasi-plurisubharmonic function (qpsh for short) from complex analysis and geometry. We define a notion of qpsh function on a valuation space associated to a quite general scheme. We then define the multiplier ideals of these functions and prove some basic results about them, such as subadditivity property, the approximation theorem. We also treat some applications in complex algebraic geometry.
Income Smoothing as Rational Equilibrium Behavior ?

In this paper I revisit the issue of real income smoothing in the setting used by Lambert (1984). I demonstrate that the particular e¤ect identi ed in his paper is actually an error: under his assumptions there is no input driven equilibrium income smoothing of the type he suggests. There are, however, several other drivers of equilibrium behavior ignored in that paper. In this paper I identify those and for the particular model structure show that when all e¤ects are considered together there is little support for the suggestion that second-best earnings generally is being smoothed through the equilibrium behavior
Pharmacological analysis of ionotropic glutamate and GABA receptor function in neuronal circuits of the zebrafish olfactory bulb Inaugural –

In the olfactory bulb and other brain areas, basic cellular and synaptic properties of individual neurons have been studied extensively in reduced preparations. Nevertheless, it is still poorly understood how intactions among multiple neurons shape spatio-temporal activity patterns and give rise to the computational properties of the the intact circuit. In this thesis, I used pharmacological manipulations of excitatory and inhibitory neurotransmitter receptors to examine the synaptic interactions underlying spontaneous and odor-evoked activity patterns in the intact OB of zebrafish. Electrophysiological and conventional and two-photon calcium imaging methods were used to record activity from the principal neurons of the OB (mitral cells), their sensory input, and local interneurons. The combined blockade of AMPA/kainate and NMDA receptors abolished odorevoked excitation of mitral cells (MCs), indicating that sensory input to the OB is mediated by ionotropic glutamate receptors. Surprisingly, however, the blockade of AMPA/Kainiate receptors alone increased the mean response of MCs and decreased the mean response of interneurons (INs). The blockade of NMDA receptors alone caused little or no change in the mean responses of MCs and INs. In addition, antagonists of both glutamate receptor types had diverse effects on the magnitude and time course of individual MC and IN responses and, thus, changed spatio-temporal activity patterns across neuronal populations. The blockade of GABA(A) receptors increased spontaneous and odor evoked firing rates of mitral cells and often induced rhythmic bursting. Moreover, the blockade of, GABA(A) or AMPA/kainate receptors abolished fast oscillatory activity in the local field potential. Blockade of GABA(B) receptors reduced calcium influx into terminals of afferent sensory axons and modulated response time courses of mitral cells. These results indicate that (1) IN activity during an odor response depends mainly on AMPA/Kainiate receptor input, (2) interactions between MCs and INs regulate the total OB output activity, (3) AMPA/Kainiate receptors and GABA(A) receptors underly the synchronization of odor-dependent neuronal ensembles and (4) odor-specific patterns of OB output activity are shaped by circuits containing iGlu receptors and GABA receptors. These results provide insights into the mechanisms underlying the processing of odor-encoding activity patterns in the OB.
Application of Fast P2P Traffic Recognition Technology Based on Decision Tree in the Detection of Network Traffic Data

With the rapid development of large-scale enterprise informatization construction, the network scale has become huge and complex, and the data traffic carried by the network is increasing. Accurate network traffic identification is the basis of network management and is of great significance to enterprise informatization construction and operation and maintenance. In response to the network operation and maintenance requirements of large enterprises, this paper analyzes the network architecture and network traffic distribution of large enterprise groups from the perspective of enterprise network operators and introduces the current operation and maintenance process of enterprise network performance failures. Maintenance process optimization and reengineering are carried out to plan and find out the shortcomings of the current process links and put forward corresponding solutions. Based on the research of traffic identification in recent years, a fast P2P network traffic anomaly identification algorithm based on decision tree model is proposed, which improves the efficiency and accuracy of network traffic application identification and network traffic anomaly data identification.
Airborne validation of spatial properties measured by the CALIPSO lidar

[1] The Cloud-Aerosol Lidar Infrared Pathfinder Satellite Observations (CALIPSO) satellite provides a new and exciting opportunity to study clouds and aerosols in the Earth's atmosphere using range-resolved laser remote sensing. Following the successful launch of the CALIPSO satellite, validation flights were conducted using the long-established Cloud Physics Lidar (CPL) to verify CALIPSO's calibration and validate various CALIPSO data products. This paper presents results of the initial comparisons made between the spaceborne CALIPSO lidar and the airborne CPL. Results are presented to validate measurement sensitivity and the spatial properties reported in the CALIPSO data products. Cloud layer top determinations from CALIPSO are found to be in good agreement with those from CPL. Determinations of minimum detectable backscatter are in excellent agreement with theoretical values predicted prior to launch.
Improving Sentences with Online Policy Gradient Methods

The task of sentence completion has been an active area of research, with Seq2Seq recurrent neural network models the most popular solution. The accuracy of such models depend on the the accuracy of the corpus the model is trained on, and actively correcting a huge corpus is an expensive task. Removing the biases learnt by a model after it has been trained is also expensive. To this goal, we investigate how reinforcement learning can be used to improve an LSTM model’s performance by teaching the model to avoid the mistakes it learned in the corpus, as well as guiding the model to follow developer defined rules.
Fire Effects on Blue Grama-Pinyon-Juniper Rangeland in New Mexico.

Highlight Study of an April 1964 fire in the blue grama-pinyon-juniper vegefa. flon WPe of New Mexico showed fhaf forage producfion was reduced szgnificanfly the first year on fhe burned area huf recovered by the end of fhe second. Species composifion of herbaceous vegefafion was no* significantly affecfed. Loss of live grass crowns was fully rwovered by.fhe second year. Liffer was sigmfmntly less on the burned area all three years of fhe study. About 24% of thejuniper and 13.5% of the pinyen pme were killed by the fire. Cholla less than one ff tall were damaged more by the fire than ihose 2 *o 3 ff *a,,.
Jeopardy, Non-Public Information, and Insider Trading Around Sec 10-K and 10-Q Filings

Evidence contrasting U.S. insider trades in high- and low-jeopardy periods and across firms at high and low risk for 10b-5 litigation indicates that insiders condition their trades on foreknowledge of price-relevant public disclosures, but avoid profitable trades when the jeopardy associated with such trades is high, such as immediately before earnings announcements. Insiders avoid profitable trades before quarterly earnings are announced and sell (buy) after good (bad) news earnings announcements. Insiders trade most heavily after earnings announcements and profit from foreknowledge of price-relevant information in the forthcoming Form 10-K or 10-Q filing.
H3Rec: Higher-Order Heterogeneous and Homogeneous Interaction Modeling for Group Recommendations of Web Services

Recommendations are important web services in the era of information explosion. Particularly, group recommendations aim to suggest new items to groups such that the members of groups are likely interested in. However, existing works still suffer from sparsity and cold-start issues (e.g., cold-start groups or items) for groups with few interactions on items. Most of them model the preferences or features of entities (i.e., users, items and groups) from heterogeneous interactions (i.e., user-item, group-item and user-group interactions) between two distinct types of entities, while ignoring the homogeneous interactions (i.e., user-user, item-item and group-group interactions) between entities of one type. To this end, we propose a new model, called H3Rec, which learns the representations of entities by developing two graph embedding layers based on an interaction graph of all entities. Specifically, the two graph embedding layers make full use of the hidden information in the Higher-order Heterogeneous and Homogeneous interactions of the graph. Therefore, H3Rec can alleviate the sparsity and cold-start issues and improve the performance of group recommendations. The experimental results on two real world datasets in different domains show the superiority of H3Rec in group recommendations, especially for cold-start groups and items.
A Multivariate Approach to Dilepton Analyses in the Upgraded ALICE Detector at CERN-LHC

ALICE, the dedicated heavy-ion experiment at CERN–LHC, will undergo a major upgrade in 2019/20. This work aims to assess the feasibility of conventional and multivariate analysis techniques for low-mass dielectron measurements in Pb-Pb collisions in a scenario involving the upgraded ALICE detector with a low magnetic field (B = 0.2 T). These electron-positron pairs are promising probes for the hot and dense medium, which is created in collisions of ultra-relativistic heavy nuclei, as they traverse the medium without significant final-state modifications. Due to their small signal-to-background ratio, high-purity dielectron samples are required. They can be provided by conventional analysis methods, which are based on sequential cuts, however at the price of low signal efficiency. This work shows that existing methods can be improved by employing multivariate approaches to reject different background sources of the dielectron invariant mass spectrum. The major background components are dielectrons from photon conversion and combinatorial pairs. By implementing deep neural networks, the signal-to-background ratio can be improved by up to 60 % over existing results in the case of pure conversion rejection and up to 30 % in the case of additional suppression of all combinatorial background components. In both cases, the gain in significance is about 15 % compared to conventional approaches. Additionally, different strategies for rejecting heavy flavor pairs (i. e., dielectrons originating from cc̄ or bb̄) are studied and some of their major challenges identified. In general, it is concluded that multivariate techniques are a powerful and promising approach to dielectron analyses since they significantly improve the results over conventional methods in terms of signal-to-background ratio and significance. Moreover, these techniques remove complexity from existing implementations as they allow to (1) base the analyses on individual tracks (instead of track pairs), essentially without sacrificing analysis performance, (2) render some of the existing and involved analysis methods obsolete and, to some degree, (3) obviate the need for manual input feature engineering.
Distributional effects of energy policy: a micro-macro perspective

This work analyses the profitability of enhancing a macroeconomic framework (Computable General Equilibrium model) using microdata from household surveys and assessing distributional effects on income and consumption induced by a simulated shock. On this purpose, the modelling options range from the fragmentation of the usual representative agent in a multi-household representation to the creation of a soft-link between the household data and the macro model. A focus is presented on inequality and poverty issues in the context of environmental and energy policies. A non-behavioural microsimulation model is developed and it is used to evaluate the distributional impacts of a policy reducing fossil fuel subsidies in Indonesia. The creation of the microsimulation link begins analysing the 2007 Indonesian household survey (IFLS4, World Bank); it follows a reconciliation procedure with the Indonesian Social Accounting Matrix using the Cross-Entropy method. Around 10000 different households heterogeneous with respect to income sources and expenditure choices and consistent with the macroeconomic variables are represented in the microsimulation module. The policy scenario, implemented using ENV-Linkages model, determines a change of prices, factor remuneration and transfers. The impact of this reform on households’ welfare is analysed under two different revenue recycling schemes (unconditioned lump-sum transfer to all households and increased governmental expenditure) and highlights the heterogeneity of policy effects across households. In the first scenario the reform results strongly progressive and slightly regressive in the second one. Furthermore, the behavioural response of household to energy policy is estimated using the Indonesian household survey data. An Extended Linear Expenditure System is fitted at county level and for urban/rural households taking in account the zero expenditure bias issue. A shock corresponding to a fossil fuel phase-out policy is imposed on consumer prices. The consumption behavioural response in the ELES system, evaluated at country level and for rural and urban
Strength Indicator Based Localization of Bluetooth Devices Using Trilateration : An Improved Method for the Visually Impaired People

The instantaneous and spatial localization for visually impaired people in dynamically changing environments with unexpected hazards and obstacles, is the most demanding and challenging issue faced by the navigation systems today. Since Bluetooth cannot utilize techniques like Time Difference of Arrival (TDOA) and Time of Arrival (TOA), it uses received signal strength indicator (RSSI) to measure Receive Signal Strength (RSS). The measurements using RSSI can be improved significantly by improving the existing methodologies related to RSSI. Therefore, the current paper focuses on proposing an improved method using trilateration for localization of Bluetooth devices for visually impaired people. To validate the method, class 2 Bluetooth devices were used along with the development of a software. Experiments were then conducted to obtain surface plots that showed the signal interferences and other environmental effects. Finally, the results obtained show the surface plots for all Bluetooth modules used along with the strong and weak points depicted as per the color codes in red, yellow and blue. It was concluded that the suggested improved method of measuring RSS using trilateration helped to not only measure signal strength affectively but also highlighted how the signal strength can be influenced by atmospheric conditions such as noise, reflections, etc. Keywords—Bluetooth, indoor/outdoor localization, received signal strength indicator, visually impaired.
Understanding climate change impacts on biome and plant distributions in the Andes: Challenges and opportunities

Climate change is expected to impact mountain biodiversity by shifting species ranges and the biomes they shape. The extent and regional variation in these impacts are still poorly understood, particularly in the highly biodiverse Andes. Regional syntheses of climate change impacts on vegetation are pivotal to identify and guide research priorities. Here we review current data, knowledge and uncertainties in past, present and future climate change impacts on vegetation in the Andes.
Pre‐collisional high pressure metamorphism and nappe tectonics at active continental margins: a numerical simulation

The evolution of a subduction channel and orogenic wedge is simulated in 2D for an active continental margin, with P‐T paths being displayed for selected markers. In our simulation, subduction erosion affects the active margin and a structural pattern develops within a few tens of millions of years, with four zones from the trench into the forearc: (i) an accretionary complex of low grade metamorphic sedimentary material, (ii) a wedge of nappes with alternating upper and lower crustal provenance, and minor interleaving of oceanic or hydrated mantle material, (iii) a megascale melange composed of high pressure (HP) and ultra‐high pressure (UHP) metamorphic rocks extruded from the subduction channel, and (iv) the upward tilted frontal part of the remaining lid. The P–T paths and time scales correspond to those typically recorded in orogenic belts. The simulation shows that HP/UHP metamorphism of continental crust does not necessarily indicate collision, but that the material can be derived from the active margin by subduction erosion and extruded from the subduction channel beneath the forearc during ongoing subduction.
Cognitive Traits as Sexually Selected Fitness Indicators

The evolutionary psychologist Geoffrey Miller has argued that various features of human psychology have been sculpted, at least in part, by the evolutionary process of sexual selection via mate choice. This paper specifically examines the central claim of Miller's account, namely that certain cognitive traits have evolved to function as good genes fitness indicators. First, I expound on and clarify key foundational concepts comprising the focal hypothesis, especially condition-dependence, mutation target size, and mutation-selection balance. Second, I proceed to highlight some subtle distinctions with respect to the concepts of exaptation and adaptation, as well as Fisherian runaway selection and good genes sexual selection, all of which in turn bear importantly on the overall framework of cognitive traits as fitness indicators. Third and finally, I close out the paper by examining various conceptual and methodological criteria which are integral to identifying sexually selected adaptations, then briefly examine some empirical work that has aimed to test the hypothesis that traits such as humor and creativity function as sexually attractive fitness indicators.
In what sense ‘regional development?’: entrepreneurship, underdevelopment and strong tradition in the periphery

This paper explores whether entrepreneurship can help less successful regions to improve their regional economic situation, without all the benefits that entrepreneurship brings when being ‘stripped out’ to more successful regions. The paper uses the idea that peripheral regions possess qualities of tradition and underdevelopment, and that these help to anchor new firms into these regions, resistant to their concentration in core regions. The paper explores whether particular entrepreneurial events can be regarded as ‘densifying’ the regional entrepreneurial environment, thereby making a positive contribution to its economic development. The paper explores the role of these negative anchors to the entrepreneurial events and the densification process by following a sequence of high-technology spin-out firms in the North East of England. Using a realist methodology attempting to interview all the firms within the sequence which could be found, the paper discovers that quite positive advantages exist within these negative qualities.The paper then considers whether these processes, such as plant closure, might drive entrepreneurship in all regions.
CONNECTING THE DOTS BETWEEN NEWS ARTICLES

One of the major technical challenges being faced by us these days is of Information Overload. There is an enormous amount of data being thrown at us almost every day. This has impacted our ability to see the bigger picture in a negative way. Also, we are facing lots of difficulties in navigating between different topics and unravelling the hidden connections between them. This project aims at tackling this problem.
Wildlife Radio Telemetry: Use, Effect and Ethical Consideration with Emphasis on Birds and Mammals

Wildlife researchers have been using radio-telemetry to track wild animal movement and behavior for long time. To use this method, wild animals are captured, manipulated and carry the transmitter over an extended period of time. Hence, it is impossible to exclude short or long term negative effects of radio collars. If such effects exist, it would bring up some ethical and scientific problems; such as, the animal could suffer, if the transmitter affects the behavior of the animal, the animal would no longer be a representative sample of the non-collared population. According to Tom Regan, who specializes in animal rights, the fundamental wrong assumption about animals is the system that allows us to view animals as our resources. It is generally assumed that, as long as the ethical guidelines are applied, the effect of radio-collars animals is insignificant. The purpose of this review paper is to raise some points for understanding of radio telemetry use and impact in scientific research. I tried to see the history of radio telemetry, its effect on wildlife, its contribution in wildlife conservation, guidelines, and Ethical consideration. Different current articles were reviewed to compare the ideas. From this background I tried to answer: Is the use of wildlife telemetry morally legitimate, if Regan's theory about animal rights is correct? And finally I summarized the ethical issues raised by different scholars and gave my assumption.