Miracle-dz/UniFAR-FTUs huggingface dataset:
Learning Interface Agents

Interface agents are computer programs that employ Artificial Intelligence techniques in order to provide assistance to a user dealing with a particular computer application. The paper discusses an interface agent which has been modelled closely after the metaphor of a personal assistant. The agent learns how to assist the user by (i) observing the user's actions and imitating them, (ii) receiving user feedback when it takes wrong actions and (iii) being trained by the user on the basis of hypothetical examples. The paper discusses how this learning agent was implemented using memory-based learning and reinforcement learning techniques. It presents actual results from two prototype agents built using these techniques: one for a meeting scheduling application and one for electronic mail. It argues that the machine learning approach to building interface agents is a feasible one which has several advantages over other approaches: it provides a customized and adaptive solution which is less costly and ensures better user acceptability. The paper also argues what the advantages are of the particular learning techniques used.
Insurance and Investment Within Family Networks

In this paper family networks affecting informal insurance and investment is being studied. Panel data from the randomized evaluation of PROGRESA in rural Mexico and the information on surnames of household heads and their spouses to identify extended families have been used. Members of an extended family: 1) share risk with each other but not with households without relatives in the village; 2) invest more in their children's human capital when hit by positive income shocks, and disinvest less when hit by negative shock, and 3) have a higher long-term increase in capital, income, and consumption than households without relatives in the village. [Working Paper No. 260]
Mass Customization and Mass Production: Balancing the Portfolio

To most companies pure Mass Customization is not applicable. On the other hand, to most companies some degree of Mass Customization will be highly valuable from various viewpoints including logistics, production, product development, and marketing. By letting customers try their hand at constructing, developing and building their own, individually customized products companies realize and test realistic future challenges. Consequently, most traditional mass producing companies are facing the challenge of balancing Mass Customization and Mass Production and furthermore, do this in a dynamic perspective. This paper will address this problem based on experiences gained mainly at LEGO Company.
Conservation of nonlinear curvature perturbations on super‐Hubble scales

We consider general, non‐linear curvature perturbations on scales greater than the Hubble horizon scale by invoking an expansion in spatial gradients, the so‐called gradient expansion. After reviewing the basic properties of the gradient expansion, we derive the conservation law for non‐linear curvature perturbations for an isentropic fluid. We also define the gauge‐invariant curvature perturbation under a finite shift of time‐slicing, and derive the non‐linear genralization of the δN formalism. The results obtained are straight‐forward generalisations of those already proven in linear perturbation theory, and the equations are simple, resembling closely the first‐order equations.
Experimental validation of a general model for three phase inverters operating in healthy and faulty modes

The paper presents the experimental verification of a general mathematical model of Voltage Source Inverters (VSI) able to simulate fault conditions and which is also useful for the simulation of fault-tolerant systems for different applications. In general, in the past, the problem of faulty inverters modeling has been addressed specifically by considering faults on the different phases as separate cases. Furthermore, traditional models include only the faulty mode and not the healthy mode, so resulting then not able to predict transient phenomena. The model hereafter presented overcomes this drawback. It was formulated by introducing the concept of “healthy leg binary variables”. Such variables allow the management of both unfaulted and faulted conditions regardless of what is the faulty phase. Experimental tests were used to verify the correctness of the followed modeling approach and the ability of the model to predict transients before, during and after the application of a fault tolerant control.
Algorithms and Data Structures for Handling a Fully Flexible Refinement Approach in Mesh Generation

This paper presents new algorithms and data structures required for the generation of grids based on mixed element trees and using flexible refinement approach. Mixed elements trees is an extension of modified octrees that uses several well-shaped primitives such as cuboids, prisms, pyramids and tetrahedra as internal nodes. A flexible refinement approach fits the object geometry and fulfills the required mesh density by partitioning the elements at an optimal point at each refinement step. This allows the fitting of more general 3-D object geometries and the reduction of grid points in comparison with previous grid generators but it requires more complex algorithms and data structures in its implementation.
Predictors of Postschool Education/Training and Employment Outcomes for Youth With Disabilities

Youth with disabilities have consistently poor postschool engagement outcomes in employment and postsecondary education and training. At least once every 6 years, states are required to submit a State Performance Plan in which they report performance on the progress of students with disabilities (20 U.S.C. 1416(b)(1)). Indicator 14 requires states to collect postschool outcome data 1 year after students exit high school. The purpose of this exploratory study was to examine the impact of student-, school-, district-level, and combined (student + school + district) factors on engagement outcomes for youth with high incidence disabilities across 3 years. Findings from logistic regression analyses indicate that student-level, district-level, and combined factors were significant in predicting postschool outcomes of employment and postsecondary education.
Alcohol as a Risk Factor for Type 2 Diabetes

OBJECTIVE To clarify the dose-response relationship between alcohol consumption and type 2 diabetes. RESEARCH DESIGN AND METHODS A systematic computer-assisted and hand search was conducted to identify relevant articles with longitudinal design and quantitative measurement of alcohol consumption. Adjustment was made for the sick-quitter effect. We used fractional polynomials in a meta-regression to determine the dose-response relationships by sex and end point using lifetime abstainers as the reference group. RESULTS The search revealed 20 cohort studies that met our inclusion criteria. A U-shaped relationship was found for both sexes. Compared with lifetime abstainers, the relative risk (RR) for type 2 diabetes among men was most protective when consuming 22 g/day alcohol (RR 0.87 [95% CI 0.76–1.00]) and became deleterious at just over 60 g/day alcohol (1.01 [0.71–1.44]). Among women, consumption of 24 g/day alcohol was most protective (0.60 [0.52–0.69]) and became deleterious at about 50 g/day alcohol (1.02 [0.83–1.26]). CONCLUSIONS Our analysis confirms previous research findings that moderate alcohol consumption is protective for type 2 diabetes in men and women.
Some Notes on Modeling the Semantic Flow of Narratives

This report summarizes our investigations into modeling semantics and coherence in narratives, which has applications in many NLP tasks. We study MCTest, a recently designed task for machine comprehension, which contains multiple-answer questions about paragraph-long fictional stories. Our focus is on creating useful meaningrepresentations for modeling stories and interaction of characters in stories, which we explain thoroughly. The work on some final ideas is ongoing.
Could Legitimacy through Corporate Social Responsibility be an Antecedent for Export Performance Enhancement: an Exploratory Study

The search for better legitimacy in an institutional context within social responsible decisions is the main focus of the present work paper. This strategic tradeoff could stimulate stakeholders’ initiatives for ultimate cooperation with companies. The latter could leverage up resources managed by public institutions in order to develop better export performance. Social norms and institutional mechanisms are, however, fostered to raise legitimacy components. Thus, stakeholders use these norms and institutional processes to assess company’s legitimacy. The exploratory study depicts the likely relationship between legitimacy and export performance of small and medium enterprises (SMEs), which are deemed to be legitimate; however, social actions are ignored by interviewers
Object Detection and Localization Using Random Forest

In this paper, we present a method for object detection and localization using the technique of random forest. In the process of supervised learning to construct random forest, we use the descriptor vectors of the SIFT features as input samples and their class information as supervised information. For each leaf node of the decision tree, the offsets of local features reach this node along with their class information, and the class information of this node are stored. Therefore, all leaf nodes construct a discriminative tree-structured codebook model. In object detection, the discriminative codebook is used to estimate the object's location via a probabilistic computation called probabilistic Hough vote. The experimental results show that our algorithm can provide a better detection results even in the complicated environment such as multi-scale, multi-perspective, occlusion and strong background noise.
Distributionally constrained items in child language: the acquisition of superweak NPI shenme ‘a/some’ in Mandarin Chinese

This paper presents new experimental results obtained from 88 Mandarin speaking children (2; 11 – 4; 09; M = 3; 11; SD = 0; 6; 44 girls) in their acquisition of shenme ‘a/some’, a prototypical superweak Negative Polarity Item (NPI) that survives in nonveridical contexts only (cf. Lin Jing et al. 2014). The existence of NPIs like shenme leads to a learnability problem. Without being confronted with negative evidence, such as corrective feedback or explicit instructions on shenme ’s ungrammaticality in contexts that are not nonveridical, how can children detect shenme ’s distributional constraint? By analysing children’s performance in an elicited imitation task, this paper investigates the learnability of the superweak NPI in Mandarin Chinese. The results suggest a learning process in which Mandarin children initially analyse shenme as a mere wh- quantifier and reanalyse it as a referentially deficient quantifier later on. The wh- analysis gives rise to a distribution of shenme in wh -questions only, whereas the non-referential analysis generates shenme ’s distribution in the whole array of nonveridical contexts. The investigation of the acquisition of the Mandarin NPI shenme shows that children are able to acquire distributionally constrained items in the absence of negative evidence: they start out with a strict assumption (i.e. the wh- analysis) and switch to a less strict and generalising analysis (i.e. the non-referential analysis) later on.
Three-dimensional simulation of eccentric LWD tool response in boreholes through dipping formations

We simulate the response of logging-while-drilling (LWD) tools in complex thee-dimensional (3-D) borehole environments using a finite-difference time-domain (FDTD) scheme in cylindrical coordinates. Several techniques are applied to the FDTD algorithm to improve the computational efficiency and the modeling accuracy of more arbitrary geometries/media in well-logging problems: (1) a 3-D FDTD cylindrical grid to avoid staircasing discretization errors in the transmitter, receiver, and mandrel geometries; (2) an anisotropic-medium (unsplit) perfectly matched layer (PML) absorbing boundary condition in cylindrical coordinates is applied to the FDTD algorithm, leading to more compact grids and reduced memory requirements; (3) a simple and efficient algorithm is employed to extract frequency-domain data (phase and amplitude) from early-time FDTD data; (4) permittivity scaling is applied to overcome the Courant limit of FDTD and allow faster simulations of lower frequency tool; and (5) two locally conformal FDTD (LC-FDTD) techniques are applied to better simulate the response of logging tools in eccentric boreholes. We validate the FDTD results against the numerical mode matching method for problems where the latter is applicable, and against pseudoanalytical results for eccentric borehole problems. The comparisons show very good agreement. Results from 3-D borehole problems involving eccentric tools and dipping beds simultaneously are also included to demonstrate the robustness of the method.
The Psychophysiological Assessment of Female Sexual Function

The success of sildenafil in treating male erectile dysfunction has brought increasing attention from researchers, drug companies, and funding sponsors to develop an effective pharmacological treatment for female sexual dysfunction. Demonstrating treatment efficacy necessitates a valid and reliable index of female sexual response. The first observable sign of sexual arousal in women is vaginal lubrication and a simultaneous increase in vaginal vasocongestion. The three primary psychophysiological assessment devices that rely on indirect measures of vasocongestion are the vaginal photoplethysmograph, devices that indirectly measure heat dissipation, and pulsed-wave Doppler ultrasonography. The most widely used and studied of these is the vaginal photoplethysmograph, which detects differences in transparency of engorged and unengorged vaginal tissue using a light reflectance method. Research has demonstrated the construct validity of this device and its response specificity to sexual stimuli. However, a recurrent issue with the use of this device is the lack of correspondence between genital measures of vasocongestion and subjective reports of “feeling sexually aroused. ” This contrasts with findings in men, which generally show high concordance between subjective and physiological measures. Evidence suggests that external stimulus information (e.g., relationship issues, sexual scenarios) may play a more important role in assessing feelings of sexual arousal than do internal physiological cues. Consistent with this is the fact that men are more accurate than women at detecting physiological changes in general (e.g., heart rate, blood pressure), but only when situational cues are absent. Clearly, this raises important conceptual issues in the definition of female sexual arousal.
Securing interactions of Android applications

Android, the most used platform for smartphones, provides mechanisms to support interactions among applications that run on the same device, it also provides protection mechanisms to rule those interactions. However, developers are responsible for selecting the protection mechanisms that their applications will use and defining them as part of an application installation package; since definition is a manual task, it is prone to errors. This work proposes a tool that statically analyzes an installation package and checks if an application has a minimum set of protection mechanisms to control access from other applications to its resources. Results show that although most applications define protection mechanisms, some of them do not, exposing their resources and users to attacks.
NK Cells Respond to Pulmonary Infection with Mycobacterium tuberculosis, but Play a Minimal Role in Protection 1

Both innate and adaptive immune systems contribute to host defense against infection with Mycobacterium tuberculosis. NK cells have been associated with early resistance against intracellular pathogens and are known to be potent producers of the cytokine IFN-γ. In C57BL/6 mice infected by aerosol exposure with M. tuberculosis, NK cells increased in the lungs over the first 21 days of infection. Expansion of the NK cell subset was associated with increased expression of activation and maturation markers. In addition, NK cells isolated from the infected lungs were capable of producing IFN-γ and became positive for perforin. In vivo depletion of NK cells using a lytic Ab had no influence on bacterial load within the lungs. These findings indicate that NK cells can become activated during the early response to pulmonary tuberculosis in the mouse model and are a source of IFN-γ, but their removal does not substantially alter the expression of host resistance.
Effect of the lysophospholipid analogues edelfosine, ilmofosine and miltefosine against Leishmania amazonensis.

OBJECTIVES Analysis of the effect of edelfosine, ilmofosine and miltefosine on Leishmania amazonensis and of potential targets of these lysophospholipid analogues. METHODS Quantification and ultrastructural analysis of the effect of lysophospholipid analogues on promastigote forms and on infected peritoneal macrophages, and flow cytometry analysis of treated promastigotes labelled with propidium iodide and rhodamine 123 (Rh123). RESULTS The lysophospholipid analogues presented potent antiproliferative activity with IC50/3 days of 1.9-3.4 microM for promastigotes and 4.2-9.0 microM for intracellular amastigotes. Treatment with these analogues in Schneider medium for 1 day led to a dose-dependent decrease in Rh123 fluorescence, an effect more accentuated in edelfosine-treated parasites, suggesting interference with the potential of the mitochondrial membrane. In both forms of L. amazonensis, edelfosine induced extensive mitochondrial damage, multinucleation and, in promastigotes, also led to plasma membrane alterations, formation of autophagic structures and membranous arrangements inside the flagellar pocket. CONCLUSIONS The alkylglycerophosphocholines edelfosine and ilmofosine were more active than the alkylphosphocholine miltefosine against promastigotes and intracellular amastigotes of L. amazonensis, and ultrastructural and flow cytometry data indicate the mitochondrion as a target of edelfosine.
Finite Growth Models and the Learning of Edit Distance CostsEric

We introduce nite growth models (FGMs) and apply them to the problem of learning optimal costs for string edit distance. We present the rst algorithm that learns the optimal insertion, deletion and substitution costs from a training corpus of similar strings. Since edit distance has found widespread application, our discovery of a simple way to learn costs may lead to improved performance in many problem areas. Our approach also yields a more powerful class of learnable string edit distances. Finite growth models are acyclic stochastic automata which allow observations to be processed in many orderings and groupings { not just one-by-one in sequential order. These capabilities, not present in earlier approaches, are essential to our stochastic formulation of string edit distance, and separate our approach from the related eld of hidden Markov modeling.
An OpenFlow-based testbed for information centric networking

Information-centric networking (ICN) is a novel networking paradigm which is attracting increasing attention by both academic and industrial researchers. In fact, it promises to provide technological solutions that best fit with the way in which Internet is actually utilized. Assessment of proposed solutions require appropriate experimental testbeds. In this context OpenFlow, which has been developed to enable the deployment of novel networking solutions in the actual network infrastructure, represents a valuable tool. Accordingly, we are currently implementing an ICN solution - called CONET - for OpenFlow networks. The solution will be deployed in two testbeds, part of larger experimental OpenFlow facility distributed across Europe realized by the EU funded OFELIA project. In particular one testbed will be based on the Open vSwitch platform while the other will be deployed on NetFPGA platforms. Our implementation has been designed to easily support other ICN solutions with simple modification of the code. Basic ICN functionality that are specifically addressed in our implementation are data naming, route-by-name, and in-network caching.
Developmental Excitation of Corticothalamic Neurons by Nicotinic Acetylcholine Receptors

In this study, we show robust nicotinic excitation of pyramidal neurons in layer VI of prefrontal cortex. This layer contains the corticothalamic neurons, which gate thalamic activity and play a critical role in attention. Our experiments tested nicotinic excitation across postnatal development, using whole-cell recordings in prefrontal brain slices from rats. These experiments showed that layer VI neurons have peak nicotinic currents during the first postnatal month, a time period of intensive cortical development in rodents. We demonstrate that these currents are mediated directly by postsynaptic nicotinic receptors and can be suppressed by a competitive antagonist of α4β2* nicotinic receptors. To record from identified corticothalamic neurons, we performed stereotaxic surgery to label the neurons projecting to medial dorsal thalamus. As hypothesized, recordings from these retrogradely labeled neurons in layer VI showed prominent nicotinic currents. Finally, we examined the effects of the drug nicotine on layer VI neurons and probed for the potential involvement of the accessory subunit, α5, in their receptors. A level of nicotine similar to that found in the blood of smokers elicits a stable inward current in layer VI neurons, yet this exposure desensitizes ∼50% of the subsequent current elicited by acetylcholine. An allosteric modulator of α4β2α5 receptors resulted in a 2.5-fold potentiation of submaximal nicotinic currents. This result is consistent with the expression of the relatively rare α5 nicotinic subunit in layer VI. In summary, we show that layer VI corticothalamic neurons can be strongly excited during development by an unusual subtype of nicotinic receptor.
A Survey of Authentication and Communications Security in Online Banking

A survey was conducted to provide a state of the art of online banking authentication and communications security implementations. Between global regions the applied (single or multifactor) authentication schemes differ greatly, as well as the security of SSL/TLS implementations. Three phases for online banking development are identified. It is predicted that mobile banking will enter a third phase, characterized by the use of standard web technologies to develop mobile banking applications for different platforms. This has the potential to make mobile banking a target for attacks in a similar manner that home banking currently is.
Housing Bubbles, Herds and Frenzies: Evidence from British Housing Markets

1 In a world of uncertainty, imperfect information and irreversible decision-making, speculation and information acquisition will generate bubbles, herding and frenzies in housing demand. The instability generated will be further exacerbated by liquidity constraints and institutional change. In this paper, the influence of herds, frenzies and bubbles on housing demand is assessed in the context of housing markets in England and Wales. Econometric models of housing transactions are estimated to capture herding effects, bubbles and crashes. In addition, techniques are used to capture regime switching, with regime switches being conditioned upon political and institutional changes in UK housing mortgage markets emerging in the 1980s. The evidence presented reveals that bubbles, herding and frenzies are important phenomena in housing markets and that the housing market is more effectively modelled when these destabilising effects are introduced into the analysis. The paper concludes with some policy implications.