Miracle-dz/UniFAR-FTUs huggingface dataset:
Endogenous Political Institutions

A fundamental aspect of institutional design is how much society chooses to delegate unchecked power to its leaders. If, once elected, a leader cannot be restrained, society runs the risk of a tyranny of the majority, if not the tyranny of a dictator. If a leader faces too many ex post checks and balances, legislative action is too often blocked. As our critical constitutional choice we focus upon the size of the minority needed to block legislation, or conversely the size of the (super) majority needed to govern. We analyse both 'optimal' constitutional design and 'positive' aspects of this process. We derive several empirical implications, which we then discuss.
L’histoire de l’Acadie telle que racontée par les jeunes francophones du Nouveau-Brunswick : construction et déconstruction d’un récit historique

On the basis of a survey conducted among New Brunswick francophone students in Grade 12 by the Institut d’etudes acadiennes of the Universite de Moncton, the author offers an analysis of the relationship they have to the historical past. As part of this inquiry, students were asked to draft a composition describing the history of Acadia from its origins to the present day. A number of elements in the accounts given by these young people, especially the central place given to the events of the Deportation, demonstrate the durability of a vision of Acadian history that dates back to the second half of the 18th century as well as a pertinent understanding of the Acadian past. Resume A partir d’un sondage effectue par l’Institut d’etudes acadiennes de l’Universite de Moncton aupres des jeunes francophones du Nouveau-Brunswick de la 12e annee, l’auteur propose une analyse du rapport que ces derniers entretiennent avec le passe. Dans le cadre de cette enquete, les eleves ont ete invites a composer une redaction racontant l’histoire de l’Acadie, depuis ses debuts a nos jours. Quelques elements du recit des jeunes, notamment le role central accorde aux evenements de la Deportation, temoignent de la perennite d’une vision de l’histoire acadienne qui est vehiculee depuis la deuxieme moitie du 18e siecle et d’une connaissance pertinente du passe acadien.
Neural Network Pattern Recognition Based Non-intrusive Load Monitoring for a Residential Energy Management System

Detailed energy consumption information of household appliance is meaningful for the demand side management (DSM) and home energy conservation. In this paper, a novel non-intrusive load monitoring (NILM) method is proposed for residential energy management systems(REMS). Unlike existing NILM techniques, this method works effectively with very few smart meter measurement parameters obtained at a low sampling rate. A neural network pattern recognition (NNPR) model is utilized in the NILM system for the first time. The proposed method can detect finite-state appliances by changing the number of output neurons. Experimental results indicate that the proposed method provides a very high identification accuracy. Moreover, this method can estimate each appliance detail energy consumption effectively, which is ideal for scheduling the household appliances and participation in the demand respond (DR).
School Psychologists' Knowledge and Self-perceived Competency in Identifying, Assessing, and Treating Childhood Anxiety Disorders in the School Setting

Anxiety disorders are highly prevalent in the school setting but highly under-recognized, compared with the more outward behavioral disorders. Because of the many negative consequences of anxiety going unnoticed in children, school psychologists should be able to identify, assess, and treat children with anxiety in the school setting. This study utilized survey research to explore whether or not school psychologists felt knowledgeable and competent in identifying, assessing, and treating anxiety disorders in the school setting. Specifically, it explored whether or not there was a relationship between years of experience and levels of degree on knowledge and competence with identifying, assessing, and treating anxiety disorders. Overall results found no main effect for years of practice on knowledge and competence in identifying, assessing, and treating anxiety, and no main effect for knowledge on levels of degree in identifying anxiety. However, there were main effects found for levels of degree on knowledge and competence in assessing and treating anxiety disorders, and with competence in identifying anxiety disorders. Consistently, those with Doctoral degrees felt more knowledgeable and competent in assessing and treating anxiety disorders, and more competent in identifying anxiety disorders than did those with Masters, Masters Plus, and the Educational Specialist degree. School psychologists felt that their knowledge and competence was average, at best, in all areas. Implications for this study show that school psychologists would benefit from seeking further knowledge on anxiety disorders through workshops or through other means. Additionally, graduate training programs in school psychology need to focus on anxiety disorders in children because of their prevalence rate and because of the potential for negative outcomes. Ideas for future research will also be discussed. Table of
Cycles and synchrony : the temporal role of context in team behavior

This chapter reports on the temporal role of context on team behavior. We will argue that variables having to do with time and timing-pace, cycles, and rhythm-are key aspects of the environment that exert considerable influence on teams. The temporal lens represents a different orientation to the study of teams. Prior work has concentrated on what goes on within the team or between the team and its context. The temporal lens focuses on when behaviors arise, how quickly they take place, and the cycles with which they are aligned. By applying the concept of entrainment to teams and their environment, the chapter will portray the team context as an external pacer, rhythm setter, creator of windows of opportunity, source of interrupts, and source of the meaning of time. The chapter ends with new research directions as the external temporal lens is integrated with other aspects of group theory. * 2 This paper reports on the temporal role of context on team behavior. We will argue that variables having to do with time and timing-pace, cycles, and rhythm-are key aspects of the environment that exert considerable influence on teams. The temporal lens represents a different orientation to the study of teams. Whereas prior work has concentrated on what goes on within the team or between the team and its context the temporal lens focuses on when behaviors arise, how quickly they take place and the cycles with which they are aligned. The temporal focus can be applied to activity within the team or between the team and its context. This chapter focuses on the latter stressing that the external context, particularly the external temporal context, plays a large role in determining the nature, speed, and timing of team processes and events. While there are a number of ways of thinking about temporal effects, we focus on entrainment. Entrainment illuminates the periodicity of events and the fact that they are occurring synchronously with other events across other levels of analysis. In other words, these events take place in bundles-many of them at once-that are predictably timed. The concept of entrainment (Ancona & Chong, 1996) helps to explain how the external temporal system influences team processes and how these processes may, in turn, be linked to larger temporal patterns in the organization and external environment. This chapter begins by locating the topic of the temporal context of teams in broader group theory. We then …
Trade-offs related to ecosystem engineering: A case study on stiffness of emerging macrophytes

Biologically mediated modifications of the abiotic environment, also called ecosystem engineering, can significantly affect a broad range of ecosystems. Nevertheless, remarkably little work has focused on the costs and benefits that ecosystem engineers obtain from traits that underlie their ecosystem engineering capacity. We addressed this topic by comparing two autogenic engineers, which vary in the degree in which they affect their abiotic environment via their physical structure. That is, we compared two plant species from the intertidal coastal zone (Spartina anglica and Zostera noltii), whose shoots are exposed to similar currents and waves, but differ in the extent that they modify their environment via reduction of hydrodynamic energy. Our results indicate that there can be trade-offs related to the traits that underlies autogenic ecosystem engineering capacity. Dissipation of hydrodynamic forces from waves was roughly a factor of three higher in vegetation with stiff leaves compared to those with flexible leaves. Drag was highest and most sensitive to hydrodynamic forces in stiff vegetation that does not bend with the flow. Thus, shoot stiffness determines both the capacity to reduce hydrodynamic energy (i.e., proxy for ecosystem engineering capacity) and the drag that needs to be resisted (i.e., proxy for associated costs). Our study underlines the importance of insight in the trade-offs involved in ecosystem engineering as a first step toward understanding the adaptive nature of ecosystem engineering.
Novel Neuromodulation Techniques to Assess Interhemispheric Communication in Neural Injury and Neurodegenerative Diseases

Interhemispheric interaction has a major role in various neurobehavioral functions. Its disruption is a major contributor to the pathological changes in the setting of brain injury such as traumatic brain injury, peripheral nerve injury, and stroke, as well as neurodegenerative diseases. Because interhemispheric interaction has a crucial role in functional consequence in these neuropathological states, a review of noninvasive and state-of-the-art molecular based neuromodulation methods that focus on or have the potential to elucidate interhemispheric interaction have been performed. This yielded approximately 170 relevant articles on human subjects or animal models. There has been a recent surge of reports on noninvasive methods such as transcranial magnetic stimulation and transcranial direct current stimulation. Since these are noninvasive techniques with little to no side effects, their widespread use in clinical studies can be easily justified. The overview of novel neuromodulation methods and how they can be applied to study the role of interhemispheric communication in neural injury and neurodegenerative disease is provided. Additionally, the potential of each method in therapeutic use as well as investigating the pathophysiology of interhemispheric interaction in neurodegenerative diseases and brain injury is discussed. New technologies such as transcranial magnetic stimulation or transcranial direct current stimulation could have a great impact in understanding interhemispheric pathophysiology associated with acquired injury and neurodegenerative diseases, as well as designing improved rehabilitation therapies. Also, advances in molecular based neuromodulation techniques such as optogenetics and other chemical, thermal, and magnetic based methods provide new capabilities to stimulate or inhibit a specific brain location and a specific neuronal population.
Dutch new nature: (re)landscaping the Millingerwaard

This paper analyses how discourses of “new nature” have been implemented in the Dutch context – as a front runner of broader “rewilding” processes throughout Europe – frequently tied to imperatives of water safety. Drawing on the specific case of the Millingerwaard, we first examine how such discourses have materially, as well as socially, transformed the landscape in question. The paper then explores how these transformations have erstwhile affected those living in the area – in ways that are perceived, positively or negatively – according to varied groups of residents and users. In doing so, we critically reflect not only on “new nature” as it has been conceived within planning processes, and empirically practiced, in the Netherlands, but also how it is described and experienced by those whose lives are intimately tied to the landscape.
Transmissionless Selectively Aligned Surface-Permanent-Magnet BLDC Motor in Hybrid Electric Vehicles

An axial-flux permanent-magnet brushless motor is designed with variable stator alignment of independent stators, thus allowing field weakening via a controllable and variable generated-voltage constant. This feature is particularly valuable in vehicle traction motors with large constant-power speed ratio, where there is also a strong desire to eliminate the need for gear changes and keep the overall size of the motor drive as small as possible. The advantage of high pole count as applied to this technique is discussed, and the simulation impact on motor drive kilovoltampere, efficiency, gradability, acceleration, and maximum speed over typical driving cycles is shown.
Epigenetic Priming of AML Blasts for All-trans Retinoic Acid-Induced Differentiation by the HDAC Class-I Selective Inhibitor Entinostat

All-trans retinoic acid (ATRA) has only limited single agent activity in AML without the PML-RARα fusion (non-M3 AML). In search of a sensitizing strategy to overcome this relative ATRA resistance, we investigated the potency of the HDAC class-I selective inhibitor entinostat in AML cell lines Kasumi-1 and HL-60 and primary AML blasts. Entinostat alone induced robust differentiation of both cell lines, which was enhanced by the combination with ATRA. This “priming” effect on ATRA-induced differentiation was at least equivalent to that achieved with the DNA hypomethylating agent decitabine, and could overall be recapitulated in primary AML blasts treated ex vivo. Moreover, entinostat treatment established the activating chromatin marks acH3, acH3K9, acH4 and H3K4me3 at the promoter of the RARβ2 gene, an essential mediator of retinoic acid (RA) signaling in different solid tumor models. Similarly, RARβ2 promoter hypermethylation (which in primary blasts from 90 AML/MDS patients was surprisingly infrequent) could be partially reversed by decitabine in the two cell lines. Re-induction of the epigenetically silenced RARβ2 gene was achieved only when entinostat or decitabine were given prior to ATRA treatment. Thus in this model, reactivation of RARβ2 was not necessarily required for the differentiation effect, and pharmacological RARβ2 promoter demethylation may be a bystander phenomenon rather than an essential prerequisite for the cellular effects of decitabine when combined with ATRA. In conclusion, as a “priming” agent for non-M3 AML blasts to the differentiation-inducing effects of ATRA, entinostat is at least as active as decitabine, and both act in part independently from RARβ2. Further investigation of this treatment combination in non-M3 AML patients is therefore warranted, independently of RARβ2 gene silencing by DNA methylation.
Estimation of Hybrid HMM/MLP models

Hybrid HMM/MLP models are useful to model piecewise stationary non-linear time series. A popular way to estimate the parameters of such models is to use the E.M. algorithm thanks to the Baum and Welch, forward-backward, algorithm. In this paper, we study a convenient way to estimate the parameters thanks to differential optimization. This new method can dramatically improve the time of calculus for long time series. Hidden Markov models have been introduced by Baum and Petrie [1] to deal with speech recognition. Decades later, Hamilton [3] applies generalization of this model to the American’s GNP series. He uses indeed linear autoregressive models with Markov switching. In a previous paper [8], we show that the generalization of the Hamilton’s model with MLP as regression function gives a model with good segmentation properties on the laser time series. The main way to estimate the parameters of these models is to use the Expectation-Maximization (E.M.) algorithm to find the maximum likelihood estimator. However, E.M. algorithm is an iterative algorithm and each M-step involves differential optimization of each MLP. These iterations inside other iterations are very expensive in CPU time. In this paper we show that careful parameterization of the model yields us a direct calculus of the derivative of the log-likelihood function (the score function). We can then estimate the model with classical differential optimization algorithms.
Automatic discovery and ranking of synonyms for search keywords in the web

Search engines are an indispensable part of a web user's life. A vast majority of these web users experience difficulties caused by the keyword-based search engines such as inaccurate results for queries and irrelevant URLs even though the given keyword is present in them. Also, relevant URLs may be lost as they may have the synonym of the keyword and not the original one. This condition is known as the polysemy problem. To alleviate these problems, we propose an algorithm called automatic discovery and ranking of synonyms for search keywords in the web (ADRS). The proposed method generates a list of candidate synonyms for individual keywords by employing the relevance factor of the URLs associated with the synonyms. Then, ranking of these candidate synonyms is done using co-occurrence frequencies and various page count-based measures. One of the major advantages of our algorithm is that it is highly scalable which makes it applicable to online data on the dynamic, domain-independent and unstructured World Wide Web. The experimental results show that the best results are obtained using the proposed algorithm with WebJaccard.
Estimation of forest height, biomass and volume using support vector regression and segmentation from lidar transects and Quickbird imagery

Lidar (light detection and ranging) remote sensing can accurately characterize forest vertical structure, such as canopy height, above-ground biomass (AGB) and timber volume; however, data acquisition is expensive. To reduce costs, one potential method is to integrate (small area) lidar transects and (large extent) optical imagery to estimate forest characteristics. Typically, multiple regression is used to link variables extracted from lidar transect data and optical imagery. Height information is then generalized from the area covered by lidar transects to other areas without lidar coverage. However, multiple regression models may not fully capture the complex relationship between variables. Fortunately, Support vector regression (SVR) provides a solution to deal with such complex nonlinear problems. Using a case study in Vancouver Island, Canada, SVR was applied to generalize canopy height from lidar transect(s) to the entire study area (2601 ha) based on a segmented Quickbird image. Results show that: (i) compared to typical multiple regression models, the SVR models provided better results for estimating canopy height; (ii) by using only one lidar transect (i.e., 8.8% cover), the SVR model generates an average canopy height estimation error of 6.2 m — which is less than a British Columbia forest inventory height class (9.0 m); and (iii) the final model estimates have relatively high correlations with field data for forest canopy height (R2: 0.81), AGB (R2: 0.76) and volume (R2: 0.64), while representing dramatically reduced acquisition costs.
Hepcidin, iron status, and renal function in chronic renal failure, kidney transplantation, and hemodialysis

Hepcidin is a small defensin‐like peptide whose production by hepatocytes is modulated in response to anemia, hypoxia, or inflammation. Hepcidin could also act as an indicator of functional iron deficiency in these patients. Cross‐sectional study was performed to assess hepcidin correlations with renal function, iron status, and hsCRP in patients with chronic renal failure on conservative treatment, on hemodialyses, and in kidney transplant recipients. Iron status, complete blood count, creatinine, albumin, lipids were assessed using standard laboratory methods. GFR was estimated using MDRD formula. Hepcidin and high sensitivity CRP were measured using commercially available kits. Ferritin and hepcidin were higher in hemodialyzed patients, kidney transplant recipients, and patients with chronic renal failure over controls. In patients with chronic renal failure, hepcidin correlated significantly with total protein, albumin, creatinine, and eGRF. In kidney transplant recipients, hepcidin correlated significantly in univariate analysis, with total protein, ferritin, time after transplantation, creatinine, eGRF and tended to correlate with cholesterol. In hemodialyzed patients hepcidin, correlated significantly with triglycerides, albumin, creatinine, urea, residual renal function, and hsCRP. In healthy volunteers, hepcidin was related to triglycerides and ferritin. Multiple regression analysis in hemodialyzed patients showed that hepcidin was independently related to creatinine, triglycerides, and residual renal function. Multiple regression analysis in kidney transplant recipients showed that hepcidin was independently related only to GFR and ferritin. Elevated hepcidin in all groups of patients studied may be due to low grade inflammation, frequently encountered in this population and mainly to impaired renal function. Am. J. Hematol. , 2006. © 2006 Wiley‐Liss, Inc.
Visual guard rail detection for advanced highway assistance systems

In this paper we present a novel method to detect guard rails in highway scenarios using a stereo camera setup. In contrast to previous methods, we combine geometry information with appearance cues using a state-of-the-art feature encoding method. In our system pipeline, we follow a hough-based approach to localize potential guard rails in the image and require each detected line to fulfill linearity in depth as well as certain height expectations. To leverage the appearance information, we exploit an efficient bag-of-features representation that relies on randomized clustering forests. The effectiveness of our approach is demonstrated on a large novel dataset with pixel-level annotations of guard rails in real-world highway scenarios.
Evolution of Self-Organized Task Specialization in Robot Swarms

Division of labor is ubiquitous in biological systems, as evidenced by various forms of complex task specialization observed in both animal societies and multicellular organisms. Although clearly adaptive, the way in which division of labor first evolved remains enigmatic, as it requires the simultaneous co-occurrence of several complex traits to achieve the required degree of coordination. Recently, evolutionary swarm robotics has emerged as an excellent test bed to study the evolution of coordinated group-level behavior. Here we use this framework for the first time to study the evolutionary origin of behavioral task specialization among groups of identical robots. The scenario we study involves an advanced form of division of labor, common in insect societies and known as “task partitioning”, whereby two sets of tasks have to be carried out in sequence by different individuals. Our results show that task partitioning is favored whenever the environment has features that, when exploited, reduce switching costs and increase the net efficiency of the group, and that an optimal mix of task specialists is achieved most readily when the behavioral repertoires aimed at carrying out the different subtasks are available as pre-adapted building blocks. Nevertheless, we also show for the first time that self-organized task specialization could be evolved entirely from scratch, starting only from basic, low-level behavioral primitives, using a nature-inspired evolutionary method known as Grammatical Evolution. Remarkably, division of labor was achieved merely by selecting on overall group performance, and without providing any prior information on how the global object retrieval task was best divided into smaller subtasks. We discuss the potential of our method for engineering adaptively behaving robot swarms and interpret our results in relation to the likely path that nature took to evolve complex sociality and task specialization.