International Capital Mobility in Developing Countries vs. Industrial Countries: What do Saving-Investment Correlations Tell Us?

The finding of Feldstein and Horioka (1980) that countriesf investment rates are highly correlated with their national saving rates has by now been confirmed by many subsequent studies, even though their inference that international capital mobility nust be low has not been as widely accepted. This paper examines the statistical relationship between national saving and investment in a sample that includes not only 14 industrialized countries, but also 50 developing countries. The paper addresses some of the econometric critiques that have been aimed at the Feldstein-Horioka work. Contrary to what one would expect from consideration of capital mobility, the coefficient appears higher for industrialized countries than for developing countries, and higher after 1973 than before. Our interpretation of the saving-investment evidence is that the hypothesis of a high degree of substitutability for claims on physical capital located in different countries is not supported by the data. International substitutability for financial capital may be nigh, but this is a separate condition (which is properly tested by looking directly at rates of return). High international substitutability for bonds would imply high international substitutability for physical capital if capital were perfectly substitutable for bonds within each country, but there is no reason for this to hold, any more than there is for all goods to be perfect substitutes.

An Empirical Exploration of Exchange Rate Target-Zones

In the context of a flexible-price monetary exchange rate model and the assumption of uncovered interest parity, we obtain a measure of the fundamental determinant of exchange rates. Daily data for the European Monetary System are used to explore the importance of non-linearities in the relationship between the exchange rates and fundamentals. Many implications of existing "target-zone" exchange rate models are tested; little support is found for existing non-linear models of limited exchange rate flexibility.

A Likelihood-Free Inference Framework for Population Genetic Data using Exchangeable Neural Networks

An explosion of high-throughput DNA sequencing in the past decade has led to a surge of interest in population-scale inference with whole-genome data. Recent work in population genetics has centered on designing inference methods for relatively simple model classes, and few scalable general-purpose inference techniques exist for more realistic, complex models. To achieve this, two inferential challenges need to be addressed: (1) population data are exchangeable, calling for methods that efficiently exploit the symmetries of the data, and (2) computing likelihoods is intractable as it requires integrating over a set of correlated, extremely high-dimensional latent variables. These challenges are traditionally tackled by likelihood-free methods that use scientific simulators to generate datasets and reduce them to hand-designed, permutation-invariant summary statistics, often leading to inaccurate inference. In this work, we develop an exchangeable neural network that performs summary statistic-free, likelihood-free inference. Our framework can be applied in a black-box fashion across a variety of simulation-based tasks, both within and outside biology. We demonstrate the power of our approach on the recombination hotspot testing problem, outperforming the state-of-the-art.Comment: 9 pages, 8 figure

Separating sets of strings by finding matching patterns is almost always hard

© 2017 Elsevier B.V. We study the complexity of the problem of searching for a set of patterns that separate two given sets of strings. This problem has applications in a wide variety of areas, most notably in data mining, computational biology, and in understanding the complexity of genetic algorithms. We show that the basic problem of finding a small set of patterns that match one set of strings but do not match any string in a second set is difficult (NP-complete, W[2]-hard when parameterized by the size of the pattern set, and APX-hard). We then perform a detailed parameterized analysis of the problem, separating tractable and intractable variants. In particular we show that parameterizing by the size of pattern set and the number of strings, and the size of the alphabet and the number of strings give FPT results, amongst others

Development of a Novel Pinned Connection for Cold-Formed Steel Trusses

Cold-formed steel trusses are a popular form of construction for light-weight buildings, particularly portal frame structures, for which spans up to 25m are increasingly common. In these long span trusses, providing high strength connections with sufficient elastic stiffness is a current limitation to developing cost-effective solutions. A novel pin-jointed truss connection named the Howick Rivet Connector (HRC) has been tested, firstly in a T-joint arrangement, then in a truss assemblage to determine its reliable strength and stiffness. Results showed that the HRC performs similarly to a bolted connection in terms of failure modes observed and loads reached. Additionally, the process of installing the HRC creates a bearing fit, eliminating slip due to tolerances. The elastic stiffness and proportionality limit of trusses with HRCs installed was shown to be appreciably greater than similarly dimensioned conventional screwed systems. Finite element (FE) models of both T-joints and trusses tested showed good agreement with experimental results, particularly in the transition from elastic to inelastic behaviour. The peak loads predicted from the FE models were however not accurately determined. To better predict this, it is recommended that the HRC forming and installation process be modelled to capture geometric irregularities and inelastic distributions which were idealised

Unveiling Clusters of RNA Transcript Pairs Associated with Markers of Alzheimer's Disease Progression

Background: One primary goal of transcriptomic studies is identifying gene expression patterns correlating with disease progression. This is usually achieved by considering transcripts that independently pass an arbitrary threshold (e.g. p<0.05). In diseases involving severe perturbations of multiple molecular systems, such as Alzheimer's disease (AD), this univariate approach often results in a large list of seemingly unrelated transcripts. We utilised a powerful multivariate clustering approach to identify clusters of RNA biomarkers strongly associated with markers of AD progression. We discuss the value of considering pairs of transcripts which, in contrast to individual transcripts, helps avoid natural human transcriptome variation that can overshadow disease-related changes. Methodology/Principal Findings: We re-analysed a dataset of hippocampal transcript levels in nine controls and 22 patients with varying degrees of AD. A large-scale clustering approach determined groups of transcript probe sets that correlate strongly with measures of AD progression, including both clinical and neuropathological measures and quantifiers of the characteristic transcriptome shift from control to severe AD. This enabled identification of restricted groups of highly correlated probe sets from an initial list of 1,372 previously published by our group. We repeated this analysis on an expanded dataset that included all pair-wise combinations of the 1,372 probe sets. As clustering of this massive dataset is unfeasible using standard computational tools, we adapted and re-implemented a clustering algorithm that uses external memory algorithmic approach. This identified various pairs that strongly correlated with markers of AD progression and highlighted important biological pathways potentially involved in AD pathogenesis. Conclusions/Significance: Our analyses demonstrate that, although there exists a relatively large molecular signature of AD progression, only a small number of transcripts recurrently cluster with different markers of AD progression. Furthermore, considering the relationship between two transcripts can highlight important biological relationships that are missed when considering either transcript in isolation. © 2012 Arefin et al

Large-scale multielectrode recording and stimulation of neural activity

Large circuits of neurons are employed by the brain to encode and process information. How this encoding and processing is carried out is one of the central questions in neuroscience. Since individual neurons communicate with each other through electrical signals (action potentials), the recording of neural activity with arrays of extracellular electrodes is uniquely suited for the investigation of this question. Such recordings provide the combination of the best spatial (individual neurons) and temporal (individual action-potentials) resolutions compared to other large-scale imaging methods. Electrical stimulation of neural activity in turn has two very important applications: it enhances our understanding of neural circuits by allowing active interactions with them, and it is a basis for a large variety of neural prosthetic devices. Until recently, the state-of-the-art in neural activity recording systems consisted of several dozen electrodes with inter-electrode spacing ranging from tens to hundreds of microns. Using silicon microstrip detector expertise acquired in the field of high-energy physics, we created a unique neural activity readout and stimulation framework that consists of high-density electrode arrays, multi-channel custom-designed integrated circuits, a data acquisition system, and data-processing software. Using this framework we developed a number of neural readout and stimulation systems: (1) a 512-electrode system for recording the simultaneous activity of as many as hundreds of neurons, (2) a 61-electrode system for electrical stimulation and readout of neural activity in retinas and brain-tissue slices, and (3) a system with telemetry capabilities for recording neural activity in the intact brain of awake, naturally behaving animals. We will report on these systems, their various applications to the field of neurobiology, and novel scientific results obtained with some of them. We will also outline future directions

Laryngeal manual therapy: a preliminary study to examine its treatment effects in the management of muscle tension dysphonia

The objectives of this study were to determine appropriate acoustic and outcome measures for the evaluation of a method of laryngeal manual therapy (LMT) used in the treatment of patients with muscle tension dysphonia (MTD). The effects of this technique were also investigated. The study was based on the hypotheses that the vertical position of the larynx in the vocal tract would lower, that the quality of the voice would normalize, and that a reduction in any vocal tract discomfort (VTD) would occur after LMT. This was a small, prospective, repeated measures pilot study in which each member of the research team was "blinded" to all other stages of the study and during which all data were anonymized until the final stage of data analysis. Ten subjects presenting with MTD completed outcome measures and provided audiorecordings immediately before, immediately after, and 1 week after LMT. The Kay CSL 4150 was used for signal acquisition and for some acoustic measurements. Spectrographic evaluation was accomplished with Praat. A new perceptual, self-rating scale, the VTD scale, and a new proforma for use by the clinician for palpatory evaluation, were developed for the study. Relative average perturbation during connected speech was significantly reduced after LMT, indicating a reduction in abnormal vocal function. The severity and frequency of VTD was shown to have reduced after LMT. This pilot study showed positive evidence for LMT as a method of therapy in the treatment of hyperfunctional voice disorders. Its effects were shown to be measurable with both acoustical analysis and the VTD scale

Toward a personalized real-time diagnosis in neonatal seizure detection

The problem of creating a personalized seizure detection algorithm for newborns is tackled in this paper. A probabilistic framework for semi-supervised adaptation of a generic patient-independent neonatal seizure detector is proposed. A system that is based on a combination of patient-adaptive (generative) and patient-independent (discriminative) classifiers is designed and evaluated on a large database of unedited continuous multichannel neonatal EEG recordings of over 800 h in duration. It is shown that an improvement in the detection of neonatal seizures over the course of long EEG recordings is achievable with on-the-fly incorporation of patient-specific EEG characteristics. In the clinical setting, the employment of the developed system will maintain a seizure detection rate at 70% while halving the number of false detections per hour, from 0.4 to 0.2 FD/h. This is the first study to propose the use of online adaptation without clinical labels, to build a personalized diagnostic system for the detection of neonatal seizures

The Suaineadh Project : a stepping stone towards the deployment of large flexible structures in space

The Suaineadh project aims at testing the controlled deployment and stabilization of space web. The deployment system is based on a simple yet ingenious control of the centrifugal force that will pull each of the four daughters sections apart. The four daughters are attached onto the four corners of a square web, and will be released from their initial stowed configuration attached to a central hub. Enclosed in the central hub is a specifically designed spinning reaction wheel that controls the rotational speed with a closed loop control fed by measurements from an onboard inertial measurement sensor. Five other such sensors located within the web and central hub provide information on the surface curvature of the web, and progression of the deployment. Suaineadh is currently at an advanced stage of development: all the components are manufactured with the subsystems integrated and are presently awaiting full integration and testing. This paper will present the current status of the Suaineadh project and the results of the most recent set of tests. In particular, the paper will cover the overall mechanical design of the system, the electrical and sensor assemblies, the communication and power systems and the spinning wheel with its control system