Miracle-dz/UniFAR-FTUs huggingface dataset:
Two Approaches to Parsing the Heterogeneity of Psychopathy

High crime rates, growing jail populations, and the escalating costs of incarceration have placed pressure on researchers and clinicians to better understand persistent criminal offenders (Beck & Gilliard, 1995). One such group of particular interest to forensic psychologists is psychopathic individuals. To date, there exists a significant body of literature suggesting that this group engages in a wide variety of antisocial acts and demonstrates limited change following rehabilitative interventions (Hart & Hare, 1997; Hart, 1998). As a result, psychopathic individuals represent a large cost to society, and psychologists are interested in finding effective interventions to manage their problematic behaviors. In this paper, we suggest that psychologists focus on more specific manifestations and etiologies of psychopathy in order to develop effective interventions. We believe that such a focus would involve (a) questioning the assumption that psychopathy (as measured by Hare’s Psychopathy Checklist-Revised; PCL-R; 1991) is an etiologically homogeneous entity, (b) identifying etiologically distinct variants of PCL-R psychopathy for study, and (c) specifying etiological mechanisms that may suggest tangible treatment targets. We also discuss two different, but compatible, methods we believe may be helpful in identifying etiological variants of PCL-R psychopathy: (a) using general personality theory to identify maladaptive traits that may produce psychopathic behavior and (b) identifying specific bio-psychological deficits capable of accounting for psychopathic behavior.
The Organization of African Unity

T H E Organization of African Unity (OAU) reflects the realities and contradictions in the continent of Africa. Three factors make the OA-U unique among regional organizations that exist and function today. First, the OAU is the largest among regional organizations, and it comprises nearly 50 member states' in a continent-wide system. Second, it is the newest and also the poorest of such organizations. Third, there is no big-Power domination of the system, at the time the operational context of OAU is much more international than that of the other regional organizations such as the Organization of American States.2 These factors have greatly influenced the evolution of'OAU in the past. This paper seeks to reassess the record of the Organization in the background of its historical evolution and operational context.
HUGIN - A Shell for Building Bayesian Belief Universes for Expert Systems

Causal probabilistic networks have proved to be a useful knowledge representation tool for modelling domains where causal relations in a broad sense are a natural way of relating domain objects and where uncertainty is inherited in these relations. This paper outlines an implementation the HUGIN shell - for handling a domain model expressed by a causal probabilistic network. The only topological restriction imposed on the network is that, it must not contain any directed loops. The approach is illustrated step by step by solving a genetic breeding problem. A graph representation of the domain model is interactively created by using instances of the basic network components-- nodes and arcs--as building blocks. This structure, together with the quantitative relations between nodes and their immediate causes expressed as conditional probabilities, are automatically transformed into a tree structure, a junction tree. Here a computationally efficient and conceptually simple algebra of Bayesian belief universes supports incorporation of new evidence, propagation of information, and calculation of revised beliefs in the states of the nodes in the network. Finally, as an exam ple of a real world application, MUNIN an expert system for electromyography is discussed.
Molecular characterization of Tn5-induced symbiotic (Fix-) mutants of Rhizobium meliloti

To investigate the expression of specific symbiotic genes during the development of nitrogen-fixing root nodules, we conducted a systematic analysis of nodule-specific proteins and RNAs produced after the inoculation of alfalfa roots with a series of Rhizobium meliloti mutants generated by site-directed transposon Tn5 mutagenesis. The mutagenized region of the Rhizobium genome covered approximately 10 kilobases and included the region encoding the nitrogenase polypeptides. All mutant strains that were analyzed produced nodules, but with several strains the nodules failed to fix nitrogen (Nod+ Fix- phenotype). All Fix- nodules accumulated reduced levels of the host plant protein leghemoglobin. In addition, Tn5 insertions in the nitrogenase operon (nifHDK genes) eliminated some or all of the nitrogenase polypeptides and nifHDK RNA transcripts, depending on the site of insertion. Finally, mutation of a region approximately 5 kilobases upstream from the nitrogenase operon resulted in the absence of all three nitrogenase polypeptides and their corresponding RNAs, suggesting that this region may serve a regulatory function during nitrogen fixation. The studies presented here indicate that site-directed mutagenesis coupled with biochemical analysis of nodule proteins and RNAs allows the identification of products of specific gene regions as well as the assignment of specific functions to previously unidentified regions of the R. meliloti genome.
Risk Factors for Psychiatric Complications after Deep Brain Stimulation in Patients with Parkinson’s Disease: An Observational Study

Background: Deep brain stimulation (DBS) of the subthalamic nucleus is an effective treatment option for patients with Parkinson’s disease (PD). The risk factors associated with the occurrence of psychiatric symptoms have not been completely elucidated. Methods: We conducted a naturalistic observational study on patients with PD who would be subjected to DBS. Clinical data, including motor functions, cognitive functions, mental status, and daily dosage of anti-PD drugs were monitored. A psychiatrist evaluated their psychiatric symptoms at the initial assessment, three months, and one year after DBS. Results: We evaluated 44 participants with PD, of which 32 were subjected to DBS. Thirteen participants were diagnosed with mental disorders at the initial assessment. Twenty-six patients were reassessed at three months after surgery, and 19 participants were reassessed at one year. At three months, the motor function of the participants was significantly improved, and the mean anti-PD drug dose was significantly decreased. Sixteen participants were experiencing some psychiatric symptoms, of which 12 were considered as worsened due to DBS, whereas 6 participants experienced improved mental state. At one year, 6 participants were suffering from some psychiatric symptoms caused by DBS, whereas improvement was observed in 6 participants. An exploratory analysis revealed that participants without dopamine dysregulation syndrome (DDS) at the screening were likely to improve their psychiatric symptoms. Conclusion: Although DBS caused some psychiatric complications, mental status was improved in some patients in a longitudinal course. DDS is possible to predict poor outcome in psychiatric complication after DBS in PD patients.
Vitamin D Prevents Endothelial Progenitor Cell Dysfunction Induced by Sera from Women with Preeclampsia or Conditioned Media from Hypoxic Placenta

Context Placenta-derived circulating factors contribute to the maternal endothelial dysfunction underlying preeclampsia. Endothelial colony forming cells (ECFC), a sub-population of endothelial progenitor cells (EPCs), are thought to be involved in vasculogenesis and endothelial repair. Low vitamin D concentrations are associated with an increased risk for preeclampsia. Objective We hypothesized that the function of human fetal ECFCs in culture would be suppressed by exposure to preeclampsia-related factors–preeclampsia serum or hypoxic placental conditioned medium– in a fashion reversed by vitamin D. Design, Setting, Patients ECFCs were isolated from cord blood of uncomplicated pregnancies and expanded in culture. Uncomplicated pregnancy villous placenta in explant culture were exposed to either 2% (hypoxic), 8% (normoxic) or 21% (hyperoxic) O2 for 48 h, after which the conditioned media (CM) was collected. Outcome Measures ECFC tubule formation (Matrigel assay) and migration were examined in the presence of either maternal serum from preeclampsia cases or uncomplicated pregnancy controls, or pooled CM, in the presence or absence of 1,25(OH)2 vitamin D3. Results 1,25(OH)2 vitamin D3 reversed the adverse effects of preeclampsia serum or CM from hypoxic placenta on ECFCs capillary-tube formation and migration. Silencing of VDR expression by VDR siRNA, VDR blockade, or VEGF pathway blockade reduced ECFC functional abilities. Effects of VDR or VEGF blockade were partially prevented by vitamin D. Conclusion Vitamin D promotes the capillary-like tubule formation and migration of ECFCs in culture, minimizing the negative effects of exposure to preeclampsia-related factors. Further evaluation of the role of vitamin D in ECFC regulation and preeclampsia is warranted.
Activity and viability of polycyclic aromatic hydrocarbon‐degrading Sphingomonas sp. LB126 in a DC‐electrical field typical for electrobioremediation measures

There has been growing interest in employing electro‐bioremediation, a hybrid technology of bioremediation and electrokinetics for the treatment of contaminated soil. Knowledge however on the effect of weak electrokinetic conditions on the activity and viability of pollutant‐degrading microorganisms is scarce. Here we present data about the influence of direct current (DC) on the membrane integrity, adenosine triphosphate (ATP) pools, physico‐chemical cell surface properties, degradation kinetics and culturability of fluorene‐degrading Sphingomonas sp. LB126. Flow cytometry was applied to quantify the uptake of propidium iodide (PI) and the membrane potential‐related fluorescence intensities (MPRFI) of individual cells within a population. Adenosine tri‐phosphate contents and fluorene biodegradation rates of bulk cultures were determined and expressed on a per cell basis. The cells' surface hydrophobicity and electric charge were assessed by contact angle and zeta potential measurements respectively. Relative to the control, DC‐exposed cells exhibited up to 60% elevated intracellular ATP levels and yet remained unaffected on all other levels of cellular integrity and functionality tested. Our data suggest that direct current (X = 1 V cm−1; J = 10.2 mA cm−2) as typically used for electrobioremediation measures has no negative effect on the activity of the polycyclic aromatic hydrocarbon (PAH)‐degrading soil microorganism, thereby filling a serious gap of the current knowledge of the electrobioremediation methodology.
Personalized document ranking: Exploiting evidence from multiple user interests for profiling and retrieval

The goal of personalization in information retrieval is to tailor the search engine results to the specific goals, preferences and general interests of the users. We propose a novel model for both user profiling and document ranking that consider the user interests as sources of evidence in order to tune the accuracy of the documents returned in response to the user query. User profiling is performed by managing the user search history using statistical based operators in order to highlight the user short-term interests seen as surrogates for building the long-term ones. The document ranking model's foundation comes from influence diagrams which are extension of Bayesian graphs, dedicated to decision-making problems. Hence, query evaluation is carried out as an inference process that aims at computing an aggregated utility of a document by considering its relevance to the query but also the corresponding utility with regard to the user's topics of interest. Experimental results using enhanced TREC collections indicate that our personalized retrieval model is effective.
Environmental change, hydrate dissociation, and submarine slope failure along continental margins: the role of saturation anomalies in landslide triggering

Submarine landslides occur along active and passive continental margins and are potentially triggered by numerous factors including the dissociation of gas hydrates. The hazard produced by such landslides can damage infrastructure (oil platforms, telecommunication lines), generate tsunamis, and cause a catastrophic release of methane to the atmosphere and ocean. Here we develop numerical models to identify the conditions under which the dissociation of gas hydrates can trigger submarine landslides. We generate a steady state distribution of hydrates in a 1D sediment column and then dissociate these hydrates by perturbing the sea floor conditions (i.e. change in ocean bottom temperature or sea level). We focus on the dissociation of highconcentration hydrate anomalies (i.e. lenses and nodules) at fine to coarse-grained stratigraphic boundaries that are subject to large changes in sediment permeability and cohesion over small distances. Our numerical models track the evolution of the pore-water pressure as solid hydrate anomalies decay, which can induce rapid consolidation of the sediments, and also enhance fluid flow by modifying the average density of the pore fluids. We use an infinite-slope analysis as a prelude to development of a rate and state friction approximation to quantify whether these changes in pore-water pressure or cohesion can decrease the sediment strength enough to result in immediate slope failure, or bring the system closer to failure. Our results indicate that changes in effective stress ranging from kPa to MPa are required to trigger slope failure.
Asymptotic optimality of maximum pressure policies in stochastic processing networks.

We consider a class of stochastic processing networks. Assume that the networks satisfy a complete resource pooling condition. We prove that each maximum pressure policy asymptotically minimizes the workload process in a stochastic processing network in heavy traffic. We also show that, under each quadratic holding cost structure, there is a maximum pressure policy that asymptotically minimizes the holding cost. A key to the optimality proofs is to prove a state space collapse result and a heavy traffic limit theorem for the network processes under a maximum pressure policy. We extend a framework of Bramson [Queueing Systems Theory Appl. 30 (1998) 89–148] and Williams [Queueing Systems Theory Appl. 30 (1998b) 5–25] from the multiclass queueing network setting to the stochastic processing network setting to prove the state space collapse result and the heavy traffic limit theorem. The extension can be adapted to other studies of stochastic processing networks. 1. Introduction. This paper is a continuation of Dai and Lin (2005), in which maximum pressure policies are shown to be throughput optimal for a class of stochastic processing networks. Throughput optimality is an important, first-order objective for many networks, but it ignores some key secondary performance measures like queueing delays experienced by jobs in these networks. In this paper we show that maximum pressure policies enjoy additional optimality properties; they are asymptotically optimal in minimizing a certain workload or holding cost of a stochastic processing network. Stochastic processing networks have been introduced in a series of three papers by Harrison (2000, 2002, 2003). In Dai and Lin (2005) and this paper we consider a special class of Harrison’s model. This class of stochastic processing networks is much more general than multiclass queueing networks that have been a subject of intensive study in the last 20 years; see, for example, Harrison (1988), Williams
Impact of Graupel Parameterization Schemes on Idealized Bow Echo Simulations

AbstractThe effect of changes in microphysical cooling rates on bow echo development and longevity are examined through changes to graupel parameterization in the Advanced Research Weather Research and Forecasting Model (ARW-WRF). Multiple simulations are performed that test the sensitivity to different graupel size distributions as well as the complete removal of graupel. It is found that size distributions with larger and denser, but fewer, graupel hydrometeors result in a weaker cold pool due to reduced microphysical cooling rates. This yields weaker midlevel (3–6 km) buoyancy and pressure perturbations, a later onset of more elevated rear inflow, and a weaker convective updraft. The convective updraft is also slower to tilt rearward, and thus bowing occurs later. Graupel size distributions with more numerous, smaller, and lighter hydrometeors result in larger microphysical cooling rates, stronger cold pools, more intense midlevel buoyancy and pressure gradients, and earlier onset of surface-based rear.
A safe position tracking strategy for multirotor helicopters

The interest for multirotor unmanned aerial vehicles (UAVs) is currently growing due to their low cost, high maneuverability, simplified mechanics, capability to perform vertical take-off and landing as well as hovering flight. These characteristics make them a promising technology suitable for applications such as surveillance of indoor environments. The present work faces the problem of safely controlling the position trajectory of multirotor UAVs by taking into consideration a conic constraint on the total thrust vector and a linear convex constraint on the position vector. The problem is solved using a linear state-space model predictive control (MPC) strategy, whose optimization is made handy by replacing the original conic constraint set on the thrust vector by an inscribed pyramidal space, which renders a linear set of inequalities. The control vector computed by the MPC is converted into a throttle command and an attitude command. The proposed method is evaluated on the basis of Monte-Carlo simulations taking into account a random disturbance force. The simulations show the effectiveness of the method in tracking the commanded trajectory while respecting the control and position constraints. They also predict the effect of both the commanded speed and the maximum inclination constraint on the system performance.
Implementing Feedback Error Learning for FES control

Walking assist using Functional Electrical Stimulation (FES) has been studied for a quite long time to help paraplegic persons overcome their walking impairment. One of the problems of these devices is how to cope with individual dependent, time-varying, and nonlinear user's characteristics and external disturbances. In this study, Feedback Error Learning (FEL), a scheme that integrates feedback and feedforward control, was applied to FES control. As a first step, an inverted-pendulum model was used to examine the usefulness of this scheme. Next, the control of a swinging motion, using a leg model simulation, was performed. After the verification in the simulation models, an FES experiment was to investigate the applicability of this system. The data obtained from the FES experiments were used to construct a new simulation model for investigating the effect of FES in different condition. The results showed that, usability of the FEL scheme for different FES control strategies.
Local Q-linear convergence and finite-time active set identification of ADMM on a class of penalized regression problems

We study the convergence of the ADMM (Alternating Direction Method of Multipliers) algorithm on a broad range of penalized regression problems including the Lasso, Group-Lasso and Graph-Lasso,(isotropic) TV-L1, Sparse Variation, and others. First, we establish a fixed-point iteration via a nonlinear operator-which is equivalent to the ADMM iterates. We then show that this nonlinear operator is Fréchet-differentiable almost everywhere and that around each fixed point, Q-linear convergence is guaranteed, provided the spectral radius of the Jacobian of the operator at the fixed point is less than 1 (a classical result on stability). Moreover, this spectral radius is then a rate of convergence for the ADMM algorithm. Also, we show that the support of the split variable can be identified after finitely many iterations. In the anisotropic cases, we show that for sufficiently large values of the tuning parameter, we recover the optimal rates in terms of Friedrichs angles, that have appeared recently in the literature. Empirical results on various problems are also presented and discussed.
Light curve analysis of Variable stars using Fourier coefficients and Principal Component Analysis

We present an efficient and robust method of light curve analysis of variable stars. While several studies have successfully employed Fourier decomposition technique for the structural analysis of a variety of light curves, a few studies have performed a principal component analysis (PCA) by using Fourier components as inputs to reduce the dimensionality further. In this paper, we employ the PCA technique to a large database of RR Lyrae and Cepheid light curves directly and compare the results with those obtained by the Fourier decomposition technique. We show that the first few principal components (PCs) allow us to extract most of the information when the input matrix is an array of magnitudes at different epochs rather than the Fourier coefficients. The first few PCs are thus enough to reconstruct the original light curves, reducing the data dimensionality by a factor of 2 to 3 compared to the Fourier coefficients. The analysis enables us to separate out the modes of RR Lyrae stars and to look for previously known and suspected resonances of Cepheid variables. We also demonstrate that the PCA technique can be used to classify variables into different classes in an automated, unsupervised way, a feature that has immense potential for large databases of the future.
Improving Vietnamese POS tagging by integrating a rich feature set and Support Vector Machines

Part of speech (POS) tagging is fundamental in natural language processing. So far, many methods have been applied for English and the task is well solved. However, there are few studies about this problem for Vietnamese. In this paper, we evaluate common features for English POS tagging and then propose some language specific features for Vietnamese POS tagging. Experimental results on the Vietnamese Lexicography Centerpsilas research grouppsilas corpus show that our POS tagger using this feature set trained by SVM outperforms other Vietnamese POS taggers.
Determination of the Local Dark Matter Density in our Galaxy

Context. The rotation curve, the total mass and the gravitational potential of the Galaxy are sensitive measurements of the dark matter halo profile. Aims. Cuspy and cored DM halo profiles are analysed with respect to recent astronomical constraints in order to constrain the shape of the Galactic DM halo and the local DM density. Methods. All Galactic density components (luminous matter and DM) are parametrized. Then the total density distribution is constrained by astronomical observations: 1) the total mass of the Galaxy, 2) the total matter density at the position of the Sun, 3) the surface density of the visible matter, 4) the surface density of the total matter in the vicinity of the Sun, 5) the rotation speed of the Sun and 6) the shape of the velocity distribution within and above the Galactic disc. The mass model of the Galaxy is mainly constrained by the local matter density (Oort limit), the rotation speed of the Sun and the total mass of the Galaxy from tracer stars in the halo. Results. We showed from a statistical χ 2 fit to all data that the local DM density is strongly positively (negatively) correlated with the scale length of the DM halo (baryonic disc). Since these scale lengths are poorly constrained the local DM density can vary from 0.2 · �