Miracle-dz/UniFAR-FTUs huggingface dataset:
Aboa Centre for Economics

This paper examines the effects of health-oriented food tax reforms on the distribution of tax payments, food demand and health outcomes. Unlike earlier work, we also take into account the uncertainty related to both demand estimation and health estimates and report the confidence intervals for the overall health effects instead of only point estimates. Taxation of sugar leads to a statistically significant reduction in both the incidence of type 2 diabetes and coronary heart disease. The health effects appear to be most pronounced for low-income individuals, and the reforms may therefore reduce health inequality. This effect undermines the traditional regressivity argument against the heavy taxation of unhealthy food. JEL Classification: H200, I140, I180
Estimation of frequencies of multiple sinusoids: Making linear prediction perform like maximum likelihood

The frequency-estimation performance of the forward-backward linear prediction (FBLP) method of Nuttall/Uhych and Clayton, is significantly improved for short data records and low signal-to-noise ratio (SNR) by using information about the rank M of the signal correlation matrix. A source for the improvement is an implied replacement of the usual estimated correlation matrix by a least squares approximation matrix having the lower rank M. A second, related cause for the improvement is an increase in the order of the prediction filter beyond conventional limits. Computationally, the recommended signal processing is the same as for the FBLP method, except that the vector of prediction coefficients is formed from a linear combination of the M principal eigenvectors of the estimated correlation matrix. Alternatively, singular value decomposition can be used in the implementation. In one special case, which we call the Kumaresan-Prony (KP) case, the new prediction coefficients can be calculated in a very simple way. Philosophically, the improvement can be considered to result from a preliminary estimation of the explainable, predictable components of the data, rather than attempting to explain all of the observed data by linear prediction.
Critical realist approaches to global learning: A focus on education for sustainability

Critical realism offers a useful epistemology and ontology for conceptualizing theoretical and methodological considerations in global learning and may help to bridge the quantitative/qualitative divide that plagues social science. This article elaborates critical realist principles, concepts and methodologies to explain how they can be employed within global learning, with examples from education for sustainability.
The WAY ahead: entity rendezvous through mobile agents

The Where Are You (WAY) system is a simple yet effective application for assisting mobile users in the performance of a variety of routine tasks. In particular one of the most common and costly usage of mobile devices is the synchronisation and rendezvous of people. The WAY system supports the mobile citizen in the location, tracking and rendezvousing with a variety of moving entities. WAY distinguishes and differentiates itself from other context sensitive service systems through its adoption of an agent oriented approach. We attempt to provide an alternate solution to this all too familiar problem, by employing an amalgamation of numerous appropriate technologies. These include context-aware mobile computing, geographic information systems (GIS), and mobile agent based technologies. System functionality is delivered through a collection of mobile lightweight intentional agents, which take cognisance of the memory and processing restrictions of personal digital assistants (PDAs). Such agents provide autonomous decision making capabilities and can amongst other things make decisions as to their location within a wireless topology and where necessary activate migration.
SIGMA POINT-BASED FASTSLAM : SOLUTION TO SLAM PROBLEM

This paper proposes a reduced sigma point transformation for a FastSLAM framework. The sigma point transformation is used to estimate robot poses in conjunction with generic particle filter used in standard FastSLAM framework. This method can estimate robot poses more consistently and accurately than the current standard particle filters, especially when involving highly nonlinear models or non-Gaussian noises. In addition, this algorithm avoids the calculation of the Jacobian for motion model which could be extremely difficult for high order systems. We proposed a sampling strategy known as a spherical simplex for sigma point transformation to estimate robot poses in FastSLAM framework. Simulation results are shown to validate the performance goals.
Predicting the Link Strength of "Newborn" Links

Measurements of online social networks (OSNs) support the common fact that not all links carry the same social value, and that the strength of each link is strictly related to the frequency of interactions between the connected users. In this paper, we investigate the predictability of the interactions on OSN links by wondering if it is possible to categorize interactive or non-interactive links at their creation time. We turn the problem into a binary classification task and introduce a set of features which leverage the temporal and topological properties of the social and interaction networks, without requiring the knowledge of the interaction history of the link. The best classifier trained on a Facebook dataset obtained 0.72 as AUC. The above performance suggests that we can distinguish between interactive/non-interactive links at the time of link creation.
A TWO-LEVEL COEVOLUTIONARY APPROACH TO MULTIDIMENSIONAL PATTERN CLASSIFICATION PROBLEMS

This paper proposes a coevolutionary classification method to discover classifiers for multidimensional pattern classification problems with continuous input variables. The classification problems may be decomposed into two subproblems, which are feature selection and classifier adaptation. A coevolutionary classification method is designed by coordinating the two sub-problems, whose performances are affected by each other. The proposed method establishes a group of partial sub-regions, defined by regional variable set, and then fits a finite number of classifiers to the data pattern by combining a genetic algorithm and a local adaptation algorithm in every sub-region. A cycle of the cooperation loop is completed by evolving the subregions based on the evaluation results of the fitted classifiers located in the corresponding sub-regions. The classifier system has been tested with well-known data sets from the UCI machine-learning database, showing superior performance to other methods such as the nearest neighbor, decision tree, and neural networks.
Making Linux Protection Mechanisms Egalitarian with UserFS

UserFS provides egalitarian OS protection mechanisms in Linux. UserFS allows any user--not just the system administrator--to allocate Unix user IDs, to use chroot, and to set up firewall rules in order to confine untrusted code. One key idea in UserFS is representing user IDs as files in a /proc-like file system, thus allowing applications to manage user IDs like any other files, by setting permissions and passing file descriptors over Unix domain sockets. UserFS addresses several challenges in making user IDs egalitarian, including accountability, resource allocation, persistence, and UID reuse. We have ported several applications to take advantage of UserFS; by changing just tens to hundreds of lines of code, we prevented attackers from exploiting application-level vulnerabilities, such as code injection or missing ACL checks in a PHP-based wiki application. Implementing UserFS requires minimal changes to the Linux kernel--a single 3,000-line kernel module--and incurs no performance overhead for most operations, making it practical to deploy on real systems.
The Combination of High-Gain Sliding Mode Observers Used as Receivers in Secure Communication

This paper considers chaos synchronization and chaos-based secure communication problems based on high-gain sliding mode unknown input observers when the observer matching condition is not satisfied to the drive signal. An auxiliary drive signal vector which satisfies the observer matching condition is introduced and an adaptive and robust observer is developed by using the auxiliary drive signal directly to not only estimate the states but also adjust adaptively the unknown parameters and the Lipschitz constants of the nonlinear terms. A high-gain sliding mode observer is considered to exactly estimate both the auxiliary drive signals and their derivatives in a finite time only based on the original drive signal. The combination of the adaptive and robust observer and the high-gain sliding mode observer becomes the receiver in chaos-based secure communication discussion. A kind of information signal recovering method is developed based on both the state synchronization and exact estimates of the derivatives of the auxiliary drive signals. Finally, a numerical simulation example is given to illustrate the effectiveness of the proposed methods.
Extracellular Matrix Defects in Aneurysmal Fibulin-4 Mice Predispose to Lung Emphysema

Background In this study we set out to investigate the clinically observed relationship between chronic obstructive pulmonary disease (COPD) and aortic aneurysms. We tested the hypothesis that an inherited deficiency of connective tissue might play a role in the combined development of pulmonary emphysema and vascular disease. Methods We first determined the prevalence of chronic obstructive pulmonary disease in a clinical cohort of aortic aneurysms patients and arterial occlusive disease patients. Subsequently, we used a combined approach comprising pathological, functional, molecular imaging, immunological and gene expression analysis to reveal the sequence of events that culminates in pulmonary emphysema in aneurysmal Fibulin-4 deficient (Fibulin-4R) mice. Results Here we show that COPD is significantly more prevalent in aneurysm patients compared to arterial occlusive disease patients, independent of smoking, other clinical risk factors and inflammation. In addition, we demonstrate that aneurysmal Fibulin-4R/R mice display severe developmental lung emphysema, whereas Fibulin-4+/R mice acquire alveolar breakdown with age and upon infectious stress. This vicious circle is further exacerbated by the diminished antiprotease capacity of the lungs and ultimately results in the development of pulmonary emphysema. Conclusions Our experimental data identify genetic susceptibility to extracellular matrix degradation and secondary inflammation as the common mechanisms in both COPD and aneurysm formation.
Bayes to the rescue: Does the type of hypnotic induction matter?

Studies comparing different forms of hypnotic induction (e.g., indirect vs. direct induction) on responsiveness to suggestion have typically found no significant difference between induction types. However, no firm conclusion can be drawn from a nonsignificant result. In contrast, Bayes factors (Jeffreys, 1939/1961) indicate whether evidence favors H0 and against the alternative hypothesis or whether data are simply insensitive. Here, we apply Bayes factors to those nonsignificant results to decide: Does the form of hypnotic induction really not matter, does it matter, or should we suspend judgment? As the claim that different inductions are differentially effective comes mostly from clinicians, we based the Bayes factors on hypnotherapists’ judgments of expected differences between inductions. In addition, we also used empirical differences between induction versus no-induction as an estimate of the order of size of effect that could be expected between different inductions, independent of clinical judgment. As a whole, the Bayesian reanalysis of the present evidence supports the claim that additional research should be done on the influence of the induction procedure on hypnotic responsiveness (at least with regard to the inductions considered in the present study), with several exceptions.
Towards an Autonomous Free-flying Robot Fleet for Intra-vehicular Transportation of Loads in Unmanned Space Stations

The prospect of the Deep Space Gateway space station deployment in late 2020s, designed to support deep space, as well as lunar missions, raises new challenges to the space robotics community. In particular, given the expectation for this space station not to be permanently crewed, logistics operations, such as inspection and handling of material to and from automated cargo spacecraft must be handled autonomously by robots. This paper starts by discussing the challenges for such robots to be able to perform loading and unloading operations to and from a cargo spacecraft docked to the station. The paper proceeds by presenting the current research being carried out at the Institute for Systems and Robotics (ISR-Lisbon) on this problem. In this context, we will first review the design of Space CoBot, a free-flyer robot for intra-vehicular operations, designed for collaborative tasks including mobile manipulation. Then, we will present initial work on the problem of object tracking and grasping using convergent controllers. And finally, our current work on load inertial parameter estimation using excitatory trajectories will be presented. Both object tracking and grasping, and the load inertial parameter estimation work are platform agnostic, meaning that they can be evaluated in current free-flyer platforms. We expect this work to produce concrete steps towards the autonomous operation of mobile service robots inside space stations.
Centrosome Motility Is Essential for Initial Axon Formation in the Neocortex

The mechanisms underlying the normal development of neuronal morphology remain a fundamental question in neurobiology. Studies in cultured neurons have suggested that the position of the centrosome and the Golgi may predict the site of axon outgrowth. During neuronal migration in the developing cortex, however, the centrosome and Golgi are oriented toward the cortical plate at a time when axons grow toward the ventricular zone. In the current work, we use in situ live imaging to demonstrate that the centrosome and the accompanying polarized cytoplasm exhibit apical translocation in newborn cortical neurons preceding initial axon outgrowth. Disruption of centrosomal activity or downregulation of the centriolar satellite protein PCM-1 affects axon formation. We further show that downregulation of the centrosomal protein Cep120 impairs microtubule organization, resulting in increased centrosome motility. Decreased centrosome motility resulting from microtubule stabilization causes an aberrant centrosomal localization, leading to misplaced axonal outgrowth. Our results reveal the dynamic nature of the centrosome in developing cortical neurons, and implicate centrosome translocation and microtubule organization during the multipolar stage as important determinants of axon formation.
Targeting credit through community members Latest version available here

Delegating the allocation of public resources to community members is an increasingly popular form of delivering public resources in developing countries. Ho wever, this approach is associated with the tradeoff between improved information about potential ben eficiaries and favoritism towards local elites, which could be strengthened in the context of credit. Unlike targeting cash transfers to the poor, the optimal targeting of credit is a more complex problem involv ing issues of productivity, repayment, and market responses: This paper analyzes this problem using a l ar e-scale lending program, the Thai Million Baht Credit Fund, which decentralizes the allocation o f loans to an elected group of community members, and provides three main results. First, exploitin g a long and detailed panel, I recover preprogram structural estimates of household productivity an d fi d that resources from the program were not allocated to high-productivity, poor households, whic h is inconsistent with poverty and productive efficiency as targeting criteria. Second, using socioecono mic networks data, I show that actual targeting is strongly driven by connections to village elites and is re lated to lower program profitability, which suggests favoritism as a reason for mistargeting. Finally, I ex ploit quasi-experimental variation in the rollout of the program and uncover evidence that, in general equilib ri m, informal credit markets compensate for targeting distortions by redirecting credit towards un co nected households, albeit at higher interest rates than those provided by the program. The results highli ght the limitations of community-driven approaches to program delivery and the role of markets in att e uating potential targeting errors.
Control of apico–basal epithelial polarity by the microtubule minus-end-binding protein CAMSAP3 and spectraplakin ACF7

ABSTRACT The microtubule cytoskeleton regulates cell polarity by spatially organizing membrane trafficking and signaling processes. In epithelial cells, microtubules form parallel arrays aligned along the apico–basal axis, and recent work has demonstrated that the members of CAMSAP/Patronin family control apical tethering of microtubule minus ends. Here, we show that in mammalian intestinal epithelial cells, the spectraplakin ACF7 (also known as MACF1) specifically binds to CAMSAP3 and is required for the apical localization of CAMSAP3-decorated microtubule minus ends. Loss of ACF7 but not of CAMSAP3 or its homolog CAMSAP2 affected the formation of polarized epithelial cysts in three-dimensional cultures. In short-term epithelial polarization assays, knockout of CAMSAP3, but not of CAMSAP2, caused microtubule re-organization into a more radial centrosomal array, redistribution of Rab11-positive (also known as Rab11A) endosomes from the apical cell surface to the pericentrosomal region and inhibition of actin brush border formation at the apical side of the cell. We conclude that ACF7 is an important regulator of apico–basal polarity in mammalian intestinal cells and that a radial centrosome-centered microtubule organization can act as an inhibitor of epithelial polarity. Highlighted Article: The spectraplakin ACF7 and microtubule minus-end-stabilizing protein CAMSAP3 cooperate in organizing non-centrosomal microtubule arrays in intestinal epithelial cells.
Orthogonal Space–Time Block Codes With CSI-Assisted Amplify-and-Forward Relaying in Correlated Nakagami-$m$ Fading Channels

In this paper, the performance of multiple-input multiple-output (MIMO) dual-hop amplify-and-forward (AF) relay systems using orthogonal space-time block codes (OSTBCs) over arbitrarily correlated Nakagami- m fading channels is analyzed. In particular, closed-form expressions for the end-to-end outage probability (OP) and the symbol error probability (SEP) with arbitrary number of transceiver antennas and general correlation matrices are derived. Their mathematically tractable forms readily enable us to evaluate the performance of MIMO AF relay systems that utilize OSTBCs. For sufficiently high signal-to-noise ratios (SNRs), asymptotically tight approximations for the OP and SEP are also attained, which reveal insights into the effects of fading parameters and antenna correlation on the system's performance. Furthermore, we prove that the correlation has no impact on the achievable diversity gain, which is equal to the minimum of the sum of fading parameters between the two hops. Selected numerically evaluated results are presented, showing an excellent agreement between the proposed analysis and equivalent Monte Carlo simulations.
Bulk Sediment Q p and Q s in the Mississippi Embayment , Central United States by

We have estimated P-wave and S-wave anelastic attenuation coefficients for the thick, unconsolidated sediments of the Mississippi embayment, central United States, using the spectral distance decay of explosion P and Rayleigh waves. The sediment-trapped P wave, Psed, is observed to ranges of 80 km at 10 Hz, and 1-Hz Rayleigh waves are observed out to 130 km from a 5000-lb borehole explosion in the northern part of the embayment. Rayleigh waves of 4 Hz are seen to distances of 3 km from a smaller 50-lb explosion. Analysis of the group velocity and amplitudedistance decay of both waves yields an average Qs of 100 and Qp of 200 for embayment sediments that are independent of frequency. Scatter in the Q estimates comes from interference of multiple P-wave reverberations and Rayleigh-wave modes. The attenuation model is self-consistent in that it is the same as obtained by the analysis of synthetic seismograms using the inferred Q-values. Inferred Qp and Qs values are more than three times higher than previous estimates and imply that unconsolidated sediments of the embayment do not significantly attenuate small-strain earthquake ground motions. These estimates represent a lower bound to Q of the sediments since significant scattering is observed in the waveform data that contributes to the distance decay of wave amplitude. Higher Q values also imply that the unconsolidated sediments of the embayment will form an efficient wave guide for surface waves radiated from shallow earthquakes or large earthquakes that rupture into the sediments, producing high-amplitude, long-duration wave trains that should be considered in earthquake hazard assessments.
Linear modes of gene expression determined by independent component analysis

MOTIVATION The expression of genes is controlled by specific combinations of cellular variables. We applied Independent Component Analysis (ICA) to gene expression data, deriving a linear model based on hidden variables, which we term 'expression modes'. The expression of each gene is a linear function of the expression modes, where, according to the ICA model, the linear influences of different modes show a minimal statistical dependence, and their distributions deviate sharply from the normal distribution. RESULTS Studying cell cycle-related gene expression in yeast, we found that the dominant expression modes could be related to distinct biological functions, such as phases of the cell cycle or the mating response. Analysis of human lymphocytes revealed modes that were related to characteristic differences between cell types. With both data sets, the linear influences of the dominant modes showed distributions with large tails, indicating the existence of specifically up- and downregulated target genes. The expression modes and their influences can be used to visualize the samples and genes in low-dimensional spaces. A projection to expression modes helps to highlight particular biological functions, to reduce noise, and to compress the data in a biologically sensible way.
Effects of Weight Initialization in a Feedforward Neural Network for Classification Using a Modified Genetic Algorithm

In this paper electroencephalography (EEG) patterns are classified using a feedforward neural network trained with a modified genetic algorithm (GA). The objective is to investigate the effects of weight initialization in the neural network and to propose the best settings. Special operators like geometric ranking selection, blend-alpha crossover and non-uniform mutation are employed. For the initialization of the chromosomes the effect of the Nguyen-Widrow weight initialization and the random initialization on the training performance are compared. For the EEG corpus it is shown that the Nguyen-Widrow algorithm is more effective than the random method weight initialization when it is used with a stochastic training method. Compared to a previous study which used backpropagation as a training method, the error rate is decreased by around 10 percent if the GA is used as a training method.