Cross-orientation masking is speed invariant between ocular pathways but speed dependent within them

In human (D. H. Baker, T. S. Meese, & R. J. Summers, 2007b) and in cat (B. Li, M. R. Peterson, J. K. Thompson, T. Duong, & R. D. Freeman, 2005; F. Sengpiel & V. Vorobyov, 2005) there are at least two routes to cross-orientation suppression (XOS): a broadband, non-adaptable, monocular (within-eye) pathway and a more narrowband, adaptable interocular (between the eyes) pathway. We further characterized these two routes psychophysically by measuring the weight of suppression across spatio-temporal frequency for cross-oriented pairs of superimposed flickering Gabor patches. Masking functions were normalized to unmasked detection thresholds and fitted by a two-stage model of contrast gain control (T. S. Meese, M. A. Georgeson, & D. H. Baker, 2006) that was developed to accommodate XOS. The weight of monocular suppression was a power function of the scalar quantity ‘speed’ (temporal-frequency/spatial-frequency). This weight can be expressed as the ratio of non-oriented magno- and parvo-like mechanisms, permitting a fast-acting, early locus, as befits the urgency for action associated with high retinal speeds. In contrast, dichoptic-masking functions superimposed. Overall, this (i) provides further evidence for dissociation between the two forms of XOS in humans, and (ii) indicates that the monocular and interocular varieties of XOS are space/time scale-dependent and scale-invariant, respectively. This suggests an image-processing role for interocular XOS that is tailored to natural image statistics—very different from that of the scale-dependent (speed-dependent) monocular variety.

Role of the dsRNA-dependent protein kinase (PKR) in the attenuation of protein loss from muscle by insulin and insulin-like growth factor-I (IGF-I)

Proteolysis-inducing factor (PIF), a tumour-produced cachectic factor, induced a dose-dependent decrease in protein synthesis in murine myotubes, together with an increase in phosphorylation of eucaryotic initiation factor 2 (eIF2) on the alpha-subunit. Both insulin (1 nM) and insulin-like growth factor I (IGF-I) (13.2 nM) attenuated the depression of protein synthesis by PIF and the increased phosphorylation of eIF2alpha, by inhibiting the activation (autophosphorylation) of the dsRNA-dependent protein kinase (PKR) by induction of protein phosphatase 1. A low-molecular weight inhibitor of PKR also reversed the depression of protein synthesis by PIF to the same extent, as did insulin and IGF-I. Both insulin and IGF-I-stimulated protein synthesis in the presence of PIF, and this was attenuated by Salubrinal, an inhibitor of phospho eIF2alpha phosphatase, suggesting that at least part of this action was due to their ability to inhibit phosphorylation of eIF2alpha. Both insulin and IGF-I also attenuated the induction of protein degradation in myotubes induced by PIF, this effect was also attenuated by Salubrinal. These results suggest an alternative mechanism involving PKR to explain the effect of insulin and IGF-I on protein synthesis and degradation in skeletal muscle in the presence of catabolic factors.

Dynamic causal modeling of load-dependent modulation of effective connectivity within the verbal working memory network

Neuroimaging studies have consistently shown that working memory (WM) tasks engage a distributed neural network that primarily includes the dorsolateral prefrontal cortex, the parietal cortex, and the anterior cingulate cortex. The current challenge is to provide a mechanistic account of the changes observed in regional activity. To achieve this, we characterized neuroplastic responses in effective connectivity between these regions at increasing WM loads using dynamic causal modeling of functional magnetic resonance imaging data obtained from healthy individuals during a verbal n-back task. Our data demonstrate that increasing memory load was associated with (a) right-hemisphere dominance, (b) increasing forward (i.e., posterior to anterior) effective connectivity within the WM network, and (c) reduction in individual variability in WM network architecture resulting in the right-hemisphere forward model reaching an exceedance probability of 99% in the most demanding condition. Our results provide direct empirical support that task difficulty, in our case WM load, is a significant moderator of short-term plasticity, complementing existing theories of task-related reduction in variability in neural networks. Hum Brain Mapp, 2013. © 2013 Wiley Periodicals, Inc.

Attenuation of muscle atrophy in a murine model of cachexia by inhibition of the dsRNA-dependent protein kinase

Atrophy of skeletal muscle is due to a depression in protein synthesis and an increase in degradation. Studies in vitro have suggested that activation of the dsRNA-dependent protein kinase (PKR) may be responsible for these changes in protein synthesis and degradation. In order to evaluate whether this is also applicable to cancer cachexia the action of a PKR inhibitor on the development of cachexia has been studied in mice bearing the MAC16 tumour. Treatment of animals with the PKR inhibitor (5 mg kg-1) significantly reduced levels of phospho-PKR in muscle down to that found in non-tumour-bearing mice, and effectively attenuated the depression of body weight, with increased muscle mass, and also inhibited tumour growth. There was an increase in protein synthesis in skeletal muscle, which paralleled a decrease in eukaryotic initiation factor 2α phosphorylation. Protein degradation rates in skeletal muscle were also significantly decreased, as was proteasome activity levels and expression. Myosin levels were increased up to values found in non-tumour-bearing animals. Proteasome expression correlated with a decreased nuclear accumulation of nuclear factor-κB (NF-κB). The PKR inhibitor also significantly inhibited tumour growth, although this appeared to be a separate event from the effect on muscle wasting. These results suggest that inhibition of the autophosphorylation of PKR may represent an appropriate target for the attenuation of muscle atrophy in cancer cachexia. © 2007 Cancer Research UK.

Increased expression of proteasome subunits in skeletal muscle of cancer patients with weight loss

Atrophy of skeletal muscle is common in patients with cancer and results in increased morbidity and mortality. In order to design effective therapy the mechanism by which this occurs needs to be elucidated. Most studies suggest that the ubiquitin-proteasome proteolytic pathway is most important in intracellular proteolysis, although there have been no reports on the activity of this pathway in patients with different extents of weight loss. In this report the expression of the ubiquitin-proteasome pathway in rectus abdominis muscle has been determined in cancer patients with weight loss of 0-34% using a competitive reverse transcriptase polymerase chain reaction to measure expression of mRNA for proteasome subunits C2 and C5, while protein expression has been determined by western blotting. Overall, both C2 and C5 gene expression was increased by about three-fold in skeletal muscle of cachectic cancer patients (average weight loss 14.5 ± 2.5%), compared with that in patients without weight loss, with or without cancer. The level of gene expression was dependent on the amount of weight loss, increasing maximally for both proteasome subunits in patients with weight loss of 12-19%. Further increases in weight loss reduced expression of mRNA for both proteasome subunits, although it was still elevated in comparison with patients with no weight loss. There was no evidence for an increase in expression at weight losses less than 10%. There was a good correlation between expression of proteasome 20Sα subunits, detected by western blotting, and C2 and C5 mRNA, showing that increased gene expression resulted in increased protein synthesis. Expression of the ubiquitin conjugating enzyme, E214k, with weight loss followed a similar pattern to that of proteasome subunits. These results suggest variations in the expression of key components of the ubiquitin-proteasome pathway with weight loss of cancer patients, and suggest that another mechanism of protein degradation must be operative for patients with weight loss less than 10%. © 2004 Elsevier Ltd. All rights reserved.

A novel adaptive weight selection algorithm for multi-objective multi-agent reinforcement learning

To solve multi-objective problems, multiple reward signals are often scalarized into a single value and further processed using established single-objective problem solving techniques. While the field of multi-objective optimization has made many advances in applying scalarization techniques to obtain good solution trade-offs, the utility of applying these techniques in the multi-objective multi-agent learning domain has not yet been thoroughly investigated. Agents learn the value of their decisions by linearly scalarizing their reward signals at the local level, while acceptable system wide behaviour results. However, the non-linear relationship between weighting parameters of the scalarization function and the learned policy makes the discovery of system wide trade-offs time consuming. Our first contribution is a thorough analysis of well known scalarization schemes within the multi-objective multi-agent reinforcement learning setup. The analysed approaches intelligently explore the weight-space in order to find a wider range of system trade-offs. In our second contribution, we propose a novel adaptive weight algorithm which interacts with the underlying local multi-objective solvers and allows for a better coverage of the Pareto front. Our third contribution is the experimental validation of our approach by learning bi-objective policies in self-organising smart camera networks. We note that our algorithm (i) explores the objective space faster on many problem instances, (ii) obtained solutions that exhibit a larger hypervolume, while (iii) acquiring a greater spread in the objective space.

Fully probabilistic control for stochastic nonlinear control systems with input dependent noise

Robust controllers for nonlinear stochastic systems with functional uncertainties can be consistently designed using probabilistic control methods. In this paper a generalised probabilistic controller design for the minimisation of the Kullback-Leibler divergence between the actual joint probability density function (pdf) of the closed loop control system, and an ideal joint pdf is presented emphasising how the uncertainty can be systematically incorporated in the absence of reliable systems models. To achieve this objective all probabilistic models of the system are estimated from process data using mixture density networks (MDNs) where all the parameters of the estimated pdfs are taken to be state and control input dependent. Based on this dependency of the density parameters on the input values, explicit formulations to the construction of optimal generalised probabilistic controllers are obtained through the techniques of dynamic programming and adaptive critic methods. Using the proposed generalised probabilistic controller, the conditional joint pdfs can be made to follow the ideal ones. A simulation example is used to demonstrate the implementation of the algorithm and encouraging results are obtained.

Highest Weight Modules of W1+∞, Darboux Transformations and the Bispectral Problem

This paper is a survey of our recent results on the bispectral problem. We describe a new method for constructing bispectral algebras of any rank and illustrate the method by a series of new examples as well as by all previously known ones. Next we exhibit a close connection of the bispectral problem to the representation theory of W1+∞–algerba. This connection allows us to explain and generalise to any rank the result of Magri and Zubelli on the symmetries of the manifold of the bispectral operators of rank and order two.

A Limit Theorem for Multi-Type Subcritical Age-Dependent Branching Processes with two Types of Immigration

Марусия Н. Славчова-Божкова - В настоящата работа се обобщава една гранична теорема за докритичен многомерен разклоняващ се процес, зависещ от възрастта на частиците с два типа имиграция. Целта е да се обобщи аналогичен резултат в едномерния случай като се прилагат “coupling” метода, теория на възстановяването и регенериращи процеси.

Investigating the utility of clinical assessments to predict success with presbyopic contact lens correction

PURPOSE: To determine the utility of a range of clinical and non-clinical indicators to aid the initial selection of the optimum presbyopic contact lens. In addition, to assess whether lens preference was influenced by the visual performance compared to the other designs trialled (intra-subject) or compared to participants who preferred other designs (inter-subject). METHODS: A double-masked randomised crossover trial of Air Optix Aqua multifocal, PureVision 2 for Presbyopia, Acuvue OASYS for Presbyopia, Biofinity multifocal and monovision was conducted on 35 presbyopes (54.3±6.2years). Participant lifestyle, personality, pupil characteristics and aberrometry were assessed prior to lens fitting. After 4 weeks of wear, high and low contrast visual acuity (VA) under photopic and mesopic conditions, reading speed, Near Activity Visual Questionnaire (NAVQ) rating, subjective quality-of-vision scoring, defocus curves, stereopsis, halometry, aberrometry and ocular physiology were quantified. RESULTS: After trialling all the lenses, preference was mixed (n=12 Biofinity, n=10 monovision, n=7 Purevision, n=4 Air Optix Aqua, n=2 Oasys). Lens preference was not dependent on personality (F=1.182, p=0.323) or the hours spent working at near (p=0.535) or intermediate (p=0.759) distances. No intersubject or strong intrasubject relationships emerged between lens preference and reading speed, NAVQ rating, halo size, aberrometry or ocular physiology (p>0.05). CONCLUSIONS: Participant lifestyle and personality, ocular optics, contact lens visual performance and ocular physiology provided poor indicators of the preferred lens type after 4 weeks of wear. This is confounded by the wide range of task visual demands of presbyopes and the limited optical differences between current multifocal contact lens designs.

Valószínűség, esély, relatív súlyok. Opciók és reálopciók (Probability, chance, relative weights)

There is a long debate (going back to Keynes) how to interpret the concept of probability in economics, in business decisions, in finance. Iván Bélyácz suggested that the Black–Scholes– Merton analysis of fi nancial derivatives has a contribution to this risk vs. uncertainty debate. This article tries to interpret this suggestion, from the viewpoint of traded options, real options, Arrow–Debreu model, Heath–Jarrow–Morton model, insurance business. The article suggests making clear distinction and using different naming ● when the frequents approach and the statistics is relevant, ● when we just use consequent relative weights during the no-arbitrage pricing, and these weight are just interpreted as probabilities, ● when we just lack the necessary information, and there is a basic uncertainty in the business decision making process. The paper suggests making a sharp distinction between fi nancial derivatives used for market risk management and credit risk type derivatives (CDO, CDS, etc) in the reregulation process of the fi nancial markets.

Determining polarization dependent diffraction coefficients from building edges using FDTD method

Electromagnetic waves in suburban environment encounter multiple obstructions that shadow the signal. These waves are scattered and random in polarization. They take multiple paths that add as vectors at the portable device. Buildings have vertical and horizontal edges. Diffraction from edges has polarization dependent characteristics. In practical case, a signal transmitted from a vertically polarized high antenna will result in a significant fraction of total power in the horizontal polarization at the street level. Signal reception can be improved whenever there is a probability of receiving the signal in at least two independent ways or branches. The Finite-Difference Time-Domain (FDTD) method was applied to obtain the two and three-dimensional dyadic diffraction coefficients (soft and hard) of right-angle perfect electric conductor (PEC) wedges illuminated by a plane wave. The FDTD results were in good agreement with the asymptotic solutions obtained using Uniform Theory of Diffraction (UTD). Further, a material wedge replaced the PEC wedge and the dyadic diffraction coefficient for the same was obtained.

Enzymatic Polymerization of High Molecular Weight DNA

The use of DNA as a polymeric building material transcends its function in biology and is exciting in bionanotechnology for applications ranging from biosensing, to diagnostics, and to targeted drug delivery. These applications are enabled by DNA’s unique structural and chemical properties, embodied as a directional polyanion that exhibits molecular recognition capabilities. Hence, the efficient and precise synthesis of high molecular weight DNA materials has become key to advance DNA bionanotechnology. Current synthesis methods largely rely on either solid phase chemical synthesis or template-dependent polymerase amplification. The inherent step-by-step fashion of solid phase synthesis limits the length of the resulting DNA to typically less than 150 nucleotides. In contrast, polymerase based enzymatic synthesis methods (e.g., polymerase chain reaction) are not limited by product length, but require a DNA template to guide the synthesis. Furthermore, advanced DNA bionanotechnology requires tailorable structural and self-assembly properties. Current synthesis methods, however, often involve multiple conjugating reactions and extensive purification steps.

The research described in this dissertation aims to develop a facile method to synthesize high molecular weight, single stranded DNA (or polynucleotide) with versatile functionalities. We exploit the ability of a template-independent DNA polymerase−terminal deoxynucleotidyl transferase (TdT) to catalyze the polymerization of 2’-deoxyribonucleoside 5’-triphosphates (dNTP, monomer) from the 3’-hydroxyl group of an oligodeoxyribonucleotide (initiator). We termed this enzymatic synthesis method: TdT catalyzed enzymatic polymerization, or TcEP.

Specifically, this dissertation is structured to address three specific research aims. With the objective to generate high molecular weight polynucleotides, Specific Aim 1 studies the reaction kinetics of TcEP by investigating the polymerization of 2’-deoxythymidine 5’-triphosphates (monomer) from the 3’-hydroxyl group of oligodeoxyribothymidine (initiator) using in situ 1H NMR and fluorescent gel electrophoresis. We found that TcEP kinetics follows the “living” chain-growth polycondensation mechanism, and like in “living” polymerizations, the molecular weight of the final product is determined by the starting molar ratio of monomer to initiator. The distribution of the molecular weight is crucially influenced by the molar ratio of initiator to TdT. We developed a reaction kinetics model that allows us to quantitatively describe the reaction and predict the molecular weight of the reaction products.

Specific Aim 2 further explores TcEP’s ability to transcend homo-polynucleotide synthesis by varying the choices of initiators and monomers. We investigated the effects of initiator length and sequence on TcEP, and found that the minimum length of an effective initiator should be 10 nucleotides and that the formation of secondary structures close to the 3’-hydroxyl group can impede the polymerization reaction. We also demonstrated TcEP’s capacity to incorporate a wide range of unnatural dNTPs into the growing chain, such as, hydrophobic fluorescent dNTP and fluoro modified dNTP. By harnessing the encoded nucleotide sequence of an initiator and the chemical diversity of monomers, TcEP enables us to introduce molecular recognition capabilities and chemical functionalities on the 5’-terminus and 3’-terminus, respectively.

Building on TcEP’s synthesis capacities, in Specific Aim 3 we invented a two-step strategy to synthesize diblock amphiphilic polynucleotides, in which the first, hydrophilic block serves as a macro-initiator for the growth of the second block, comprised of natural and/or unnatural nucleotides. By tuning the hydrophilic length, we synthesized the amphiphilic diblock polynucleotides that can self-assemble into micellar structures ranging from star-like to crew-cut morphologies. The observed self-assembly behaviors agree with predictions from dissipative particle dynamics simulations as well as scaling law for polyelectrolyte block copolymers.

In summary, we developed an enzymatic synthesis method (i.e., TcEP) that enables the facile synthesis of high molecular weight polynucleotides with low polydispersity. Although we can control the nucleotide sequence only to a limited extent, TcEP offers a method to integrate an oligodeoxyribonucleotide with specific sequence at the 5’-terminus and to incorporate functional groups along the growing chains simultaneously. Additionally, we used TcEP to synthesize amphiphilic polynucleotides that display self-assemble ability. We anticipate that our facile synthesis method will not only advance molecular biology, but also invigorate materials science and bionanotechnology.

Posterior Probability Modeling and Image Classification for Archaeological Site Prospection: Building a Survey Efficacy Model for Identifying Neolithic Felsite Workshops in the Shetland Islands

The application of custom classification techniques and posterior probability modeling (PPM) using Worldview-2 multispectral imagery to archaeological field survey is presented in this paper. Research is focused on the identification of Neolithic felsite stone tool workshops in the North Mavine region of the Shetland Islands in Northern Scotland. Sample data from known workshops surveyed using differential GPS are used alongside known non-sites to train a linear discriminant analysis (LDA) classifier based on a combination of datasets including Worldview-2 bands, band difference ratios (BDR) and topographical derivatives. Principal components analysis is further used to test and reduce dimensionality caused by redundant datasets. Probability models were generated by LDA using principal components and tested with sites identified through geological field survey. Testing shows the prospective ability of this technique and significance between 0.05 and 0.01, and gain statistics between 0.90 and 0.94, higher than those obtained using maximum likelihood and random forest classifiers. Results suggest that this approach is best suited to relatively homogenous site types, and performs better with correlated data sources. Finally, by combining posterior probability models and least-cost analysis, a survey least-cost efficacy model is generated showing the utility of such approaches to archaeological field survey.

New tools for cognitive and motor rehabilitation: development and clinical validation

Nervous system disorders are associated with cognitive and motor deficits, and are responsible for the highest disability rates and global burden of disease. Their recovery paths are vulnerable and dependent on the effective combination of plastic brain tissue properties, with complex, lengthy and expensive neurorehabilitation programs. This work explores two lines of research, envisioning sustainable solutions to improve treatment of cognitive and motor deficits. Both projects were developed in parallel and shared a new sensible approach, where low-cost technologies were integrated with common clinical operative procedures. The aim was to achieve more intensive treatments under specialized monitoring, improve clinical decision-making and increase access to healthcare. The first project (articles I – III) concerned the development and evaluation of a web-based cognitive training platform (COGWEB), suitable for intensive use, either at home or at institutions, and across a wide spectrum of ages and diseases that impair cognitive functioning. It was tested for usability in a memory clinic setting and implemented in a collaborative network, comprising 41 centers and 60 professionals. An adherence and intensity study revealed a compliance of 82.8% at six months and an average of six hours/week of continued online cognitive training activities. The second project (articles IV – VI) was designed to create and validate an intelligent rehabilitation device to administer proprioceptive stimuli on the hemiparetic side of stroke patients while performing ambulatory movement characterization (SWORD). Targeted vibratory stimulation was found to be well tolerated and an automatic motor characterization system retrieved results comparable to the first items of the Wolf Motor Function Test. The global system was tested in a randomized placebo controlled trial to assess its impact on a common motor rehabilitation task in a relevant clinical environment (early post-stroke). The number of correct movements on a hand-to-mouth task was increased by an average of 7.2/minute while the probability to perform an error decreased from 1:3 to 1:9. Neurorehabilitation and neuroplasticity are shifting to more neuroscience driven approaches. Simultaneously, their final utility for patients and society is largely dependent on the development of more effective technologies that facilitate the dissemination of knowledge produced during the process. The results attained through this work represent a step forward in that direction. Their impact on the quality of rehabilitation services and public health is discussed according to clinical, technological and organizational perspectives. Such a process of thinking and oriented speculation has led to the debate of subsequent hypotheses, already being explored in novel research paths.