Miracle-dz/UniFAR-FTUs huggingface dataset:
Modeling Microwave Fully Polarimetric Passive Observations of the Sea Surface: A Neural Network Approach

The two-scale electromagnetic model is a well-established theory for simulating microwave polarimetric passive observations of a sea surface. A critical aspect is the long computational time that is required to run the forward model, which hampers the creation of large training databases or iterative simulations within retrieval algorithms. To tackle this problem, a neural network (NN) technique is proposed in this paper. In particular, we have adopted NNs to emulate a simulator named SEAWIND, which implements the two-scale model and was validated in previous works. Two training algorithms, including a regularized approach, have been considered and compared. The assessment of the proposed approach has been carried out by statistically comparing neural-network-derived simulations with SEAWIND-derived ones for two validation data sets comprising different climatic conditions, as well as by computing the azimuthal Fourier harmonic coefficients versus wind speed and atmospheric transmittance. Regressive model functions have also been used as benchmarks. This paper demonstrates the feasibility of an NN approach to efficient and effective modeling of sea-surface thermal emission and scattering.
Persian phoneme recognition using long short-term memory neural network

Recently Recurrent Neural Networks (RNNs) have shown impressive performance in sequence classification tasks. In this paper we apply Long Short-Term Memory (LSTM) network on Persian phoneme recognition. For years Hidden Markov Model (HMM) was the dominant technique in speech recognition system but after introducing LSTM, RNNs outperformed HHM-based methods. We apply LSTM and deep LSTM on FARSDAT speech database and find that both LSTM and deep LSTM outperforms HMM in Persian phoneme recognition. Our evaluation show that deep LSTM achieves 17.55% error in FARSDAT phoneme recognition on test set which to our knowledge is the best recorded result.
Design techniques for weakly constrained codes

A general method of constructing run-length limited (d, k) constrained codes from arbitrary sequences is introduced. This method is then combined with the method of guided scrambling for constructing a class of weakly constrained codes. The proposed codes are analyzed for the case of d=0 and are shown to give results which are better or comparable to those of the best available codes, however, at the cost of failure with some very low probability. For d>0, the code efficiency of the codes constructed according to the proposed method reduces significantly.
The Laminar Cortex Model: A New Continuum Cortex Model Incorporating Laminar Architecture

Local field potentials (LFPs) are widely used to study the function of local networks in the brain. They are also closely correlated with the blood-oxygen-level-dependent signal, the predominant contrast mechanism in functional magnetic resonance imaging. We developed a new laminar cortex model (LCM) to simulate the amplitude and frequency of LFPs. Our model combines the laminar architecture of the cerebral cortex and multiple continuum models to simulate the collective activity of cortical neurons. The five cortical layers (layer I, II/III, IV, V, and VI) are simulated as separate continuum models between which there are synaptic connections. The LCM was used to simulate the dynamics of the visual cortex under different conditions of visual stimulation. LFPs are reported for two kinds of visual stimulation: general visual stimulation and intermittent light stimulation. The power spectra of LFPs were calculated and compared with existing empirical data. The LCM was able to produce spontaneous LFPs exhibiting frequency-inverse (1/ƒ) power spectrum behaviour. Laminar profiles of current source density showed similarities to experimental data. General stimulation enhanced the oscillation of LFPs corresponding to gamma frequencies. During simulated intermittent light stimulation, the LCM captured the fundamental as well as high order harmonics as previously reported. The power spectrum expected with a reduction in layer IV neurons, often observed with focal cortical dysplasias associated with epilepsy was also simulated.
Phase Transitions and Complexity of Weighted Satisfiability and Other Intractable Parameterized Problems

The study of random instances of NP complete and coNP complete problems has had much impact on our understanding of the nature of hard problems. In this work, we initiate an effort to extend this line of research to random instances of intractable parameterized problems. We propose random models for a representative intractable parameterized problem, the weighted d-CNF satisfiability, and its generalization to the constraint satisfaction problem. The exact threshold for the phase transition of the proposed models is determined. Lower bounds on the time complexity of variants of the DPLL algorithm for these parameterized problems are also established. In particularly, we show that random instances of the weighted 2-CNF satisfiability, already an intractable parameterized problem, are typically easy in both of the satisfiable and unsatisfiable regions by exploiting an interesting connection between the unsatisfiability of a weighted 2-CNF formula and the existence of a Hamiltonian-cycle-like global structure.
Speeding Up Exact Solutions of Interactive Dynamic Influence Diagrams Using Action Equivalence

Interactive dynamic influence diagrams (I-DIDs) are graphical models for sequential decision making in partially observable settings shared by other agents. Algorithms for solving I-DIDs face the challenge of an exponentially growing space of candidate models ascribed to other agents, over time. Previous approach for exactly solving I-DIDs groups together models having similar solutions into behaviorally equivalent classes and updates these classes. We present a new method that, in addition to aggregating behaviorally equivalent models, further groups models that prescribe identical actions at a single time step. We show how to update these augmented classes and prove that our method is exact. The new approach enables us to bound the aggregated model space by the cardinality of other agents' actions. We evaluate its performance and provide empirical results in support.
Explorer Evidence for Widespread Degradation of Gene Control Regions in Hominid Genomes

General rights Copyright for the publications made accessible via the Edinburgh Research Explorer is retained by the author(s) and / or other copyright owners and it is a condition of accessing these publications that users recognise and abide by the legal requirements associated with these rights. Take down policy The University of Edinburgh has made every reasonable effort to ensure that Edinburgh Research Explorer content complies with UK legislation. If you believe that the public display of this file breaches copyright please contact openaccess@ed.ac. uk providing details, and we will remove access to the work immediately and investigate your claim. Although sequences containing regulatory elements located close to protein-coding genes are often only weakly conserved during evolution, comparisons of rodent genomes have implied that these sequences are subject to some selective constraints. Evolutionary conservation is particularly apparent upstream of coding sequences and in first introns, regions that are enriched for regulatory elements. By comparing the human and chimpanzee genomes, we show here that there is almost no evidence for conservation in these regions in hominids. Furthermore, we show that gene expression is diverging more rapidly in hominids than in murids per unit of neutral sequence divergence. By combining data on polymorphism levels in human noncoding DNA and the corresponding human–chimpanzee divergence, we show that the proportion of adaptive substitutions in these regions in hominids is very low. It therefore seems likely that the lack of conservation and increased rate of gene expression divergence are caused by a reduction in the effectiveness of natural selection against deleterious mutations because of the low effective population sizes of hominids. This has resulted in the accumulation of a large number of deleterious mutations in sequences containing gene control elements and hence a widespread degradation of the genome during the evolution of humans and chimpanzees. Evidence for widespread degradation of gene control regions in hominid genomes. PLoS Biol 3(2): e42.
Radar Imaging of Urban Areas by Means of Very High-Resolution SAR and Interferometric SAR

In remote-sensing applications, the monitoring of urban areas by means of synthetic aperture radar (SAR) sensors has grown into a valuable and indispensable tool. Although SAR imaging with a spatial resolution down to 1 m is widespread, a resolution as fine as 10 cm and below is offered only by very few SAR sensors worldwide. In this paper, the potential of very high-resolution radar imaging of urban areas by means of SAR and interferometric imaging will be demonstrated and discussed. Results of urban SAR imaging down to subdecimeter resolution will be shown. Even though the immanent layover situation in urban areas is an obstacle to simple image understanding, a remedy can be found by using interferometric SAR imaging. Interferometric results based on very high-resolution SAR images acquired over urban areas, partially with a severe layover situation, will be presented. The corresponding data was acquired with the phased array multifunctional imaging radar (PAMIR), the X-band demonstrator of the Research Institute for High Frequency Physics and Radar Techniques (FHR), Forschungsgesellschaft fur Angewandte Naturwissenschaften (FGAN), Wachtberg, Germany. It can be stated that high-resolution interferometric SAR will be an important basis for upcoming radar-based urban analysis.
Repetitive Extragenic Palindromic PCR for Study of Streptococcus mutans Diversity and Transmission in Human Populations

ABSTRACT Pulsed-field gel electrophoresis (PFGE) is considered the “gold standard” for molecular epidemiological study. Repetitive extragenic palindromic PCR (rep-PCR) is less time-consuming and more suitable for analyzing large numbers of bacterial strains in human populations. PFGE and rep-PCR provide comparable genotyping results for investigating Streptococcus mutans diversity and transmission.
Deep Primal-Dual Reinforcement Learning: Accelerating Actor-Critic using Bellman Duality

We develop a parameterized Primal-Dual $\pi$ Learning method based on deep neural networks for Markov decision process with large state space and off-policy reinforcement learning. In contrast to the popular Q-learning and actor-critic methods that are based on successive approximations to the nonlinear Bellman equation, our method makes primal-dual updates to the policy and value functions utilizing the fundamental linear Bellman duality. Naive parametrization of the primal-dual $\pi$ learning method using deep neural networks would encounter two major challenges: (1) each update requires computing a probability distribution over the state space and is intractable; (2) the iterates are unstable since the parameterized Lagrangian function is no longer linear. We address these challenges by proposing a relaxed Lagrangian formulation with a regularization penalty using the advantage function. We show that the dual policy update step in our method is equivalent to the policy gradient update in the actor-critic method in some special case, while the value updates differ substantially. The main advantage of the primal-dual $\pi$ learning method lies in that the value and policy updates are closely coupled together using the Bellman duality and therefore more informative. Experiments on a simple cart-pole problem show that the algorithm significantly outperforms the one-step temporal-difference actor-critic method, which is the most relevant benchmark method to compare with. We believe that the primal-dual updates to the value and policy functions would expedite the learning process. The proposed methods might open a door to more efficient algorithms and sharper theoretical analysis.
A novel dictionary-based classification algorithm for opinion mining

There has been a rapid rise in the number of users getting connected online via social networking sites. To communicate with other users and share their thoughts and opinions, online users' tend to use texts in the form of blogs, posts, tweets, messages, reviews, comments etc. Thus, there has been an immense possibility complemented with a wide gamut of research in the field of Opinion Mining or Sentiment Analysis by using textual information from online communities. Hence, there is an extensive need for different text classification algorithms and approaches to classify texts and predict sentiments correctly so as to comprehend the emotional state of the user. We have varied algorithms for text classification for predicting emotional traits. In this paper, we are proposing a novel dictionary-based algorithm that uses lexicon-based approach for opinion mining and calculates the sentiment polarity levels. Our algorithm is different from other lexicon-based algorithms in the context that it uses the three degrees of comparisons viz. positive, comparative and superlative degrees on words; for each of the positive and negative sentiment words. Our system yields an Accuracy of 81% and an F-score of 0.874 on the test dataset which is quite moderate and can be fairly accepted.
Role-based Eco-info Systems: An Organizational Theoretical View of Sustainable HCI at Work

So far, sustainable HCI has mainly focused on the domestic context, but there is a growing body of work looking at the organizational context. As in the domestic context, these works still rest on psychological theories for behaviour change used for the domestic context. We supplement this view with an organizational theory-informed approach that adopts organizational roles as a key element. We will show how a role-based analysis could be applied to uncover information needs and to give employee’s eco-feedback, which is linked to their tasks at hand. We illustrate the approach on a qualitative case study that was part of a broader, on-going action research conducted in a German production company.
Role of brain-derived neurotrophic factor in the excitatory–inhibitory imbalance during the critical period of postnatal respiratory development in the rat

The critical period of respiratory development in rats is a narrow window toward the end of the second postnatal week (P12–13), when abrupt neurochemical, electrophysiological, and ventilatory changes occur, when inhibition dominates over excitation, and when the animals’ response to hypoxia is the weakest. The goal of this study was to further test our hypothesis that a major mechanism underlying the synaptic imbalance during the critical period is a reduced expression of brain‐derived neurotrophic factor (BDNF) and its TrkB receptors. Our aims were to determine (1) that the inhibitory dominance observed in hypoglossal motoneurons during the critical period was also demonstrable in a key respiratory chemosensor, NTSVL; (2) if in vivo application of a TrkB agonist, 7,8‐DHF, would prevent, but a TrkB antagonist, ANA‐12, would accentuate the synaptic imbalance; and (3) if hypoxia would also heighten the imbalance. Our results indicate that (1) the synaptic imbalance was evident in the NTSVL during the critical period; (2) intraperitoneal injections of 7,8‐DHF prevented the synaptic imbalance during the critical period, whereas ANA‐12 in vivo accentuated such an imbalance; and (3) acute hypoxia induced the weakest response in both the amplitude and frequency of sEPSCs during the critical period, but it increased the frequency of sIPSCs during the critical period. Thus, our findings are consistent with and strengthen our hypothesis that BDNF and TrkB play a significant role in inducing a synaptic imbalance during the critical period of respiratory development in the rat.
An Empirical Study of Word Error Minimization Approaches for Mandarin Large Vocabulary Continuous Speech Recognition

This paper presents an empirical study of word error minimization approaches for Mandarin large vocabulary continuous speech recognition (LVCSR). First, the minimum phone error (MPE) criterion, which is one of the most popular discriminative training criteria, is extensively investigated for both acoustic model training and adaptation in a Mandarin LVCSR system. Second, the word error minimization (WEM) criterion, used to rescore N-best word strings, is appropriately modified for a Mandarin LVCSR system. Finally, a series of speech recognition experiments is conducted on the MATBN Mandarin Chinese broadcast news corpus. The experiment results demonstrate that the MPE training approach reduces the character error rate (CER) by 12% for a system initially trained with the maximum likelihood (ML) approach. Meanwhile, for unsupervised acoustic model adaptation, MPE-based linear regression (MPELR) adaptation outperforms conventional maximum likelihood linear regression (MLLR) in terms of CER reduction. When the WEM decoding approach is used for N-best rescoring, a slight performance gain over the conventional maximum a posteriori (MAP) decoding method is also observed.
The cytoplast concept in dividing plant cells: cytoplasmic domains and the evolution of spatially organized cell.

The unique cytokinetic apparatus of higher plant cells comprises two cytoskeletal systems: a predictive preprophase band of microtubules (MTs), which defines the future division site, and the phragmoplast, which mediates crosswall formation after mitosis. We review features of plant cell division in an evolutionary context and from the viewpoint that the cell is a domain of cytoplasm (cytoplast) organized around the nucleus by a cytoskeleton consisting of a single "tensegral" unit. The term "tensegrity" is a contraction of "tensional integrity" and the concept proposes that the whole cell is organized by an integrated cytoskeleton of tension elements (e.g., actin fibers) extended over compression-resistant elements (e.g., MTs). During cell division, a primary role of the spindle is seen as generating two cytoplasts from one with separation of chromosomes a later, derived function. The telophase spindle separates the newly forming cytoplasts and the overlap between half spindles (the shared edge of two new domains) dictates the position at which cytokinesis occurs. Wall MTs of higher plant cells, like the MT cytoskeleton in animal and protistan cells, spatially define the interphase cytoplast. Redeployment of actin and MTs into the preprophase band (PPB) is the overt signal that the boundary between two nascent cytoplasts has been delineated. The "actin-depleted zone" that marks the site of the PPB throughout mitosis may be a more persistent manifestation of this delineation of two domains of cortical actin. The growth of the phragmoplast is controlled by these domains, not just by the spindle. These domains play a major role in controlling the path of phragmoplast expansion. Primitive land plants show different morphological changes that reveal that the plane of division, with or without the PPB, has been determined well in advance of mitosis.The green alga Spirogyra suggests how the phragmoplast system might have evolved: cytokinesis starts with cleavage and then actin-related determinants stimulate and positionally control cell-plate formation in a phragmoplast arising from interzonal MTs from the spindle. Actin in the PPB of higher plants may be assembling into a potential furrow, imprinting a cleavage site whose persistent determinants (perhaps actin) align the outgrowing edge of the phragmoplast, as in Spirogyra. Cytochalasin spatially disrupts polarized mitosis and positioning of the phragmoplast. Thus, the tensegral interaction of actin with MTs (at the spindle pole and in the phragmoplast) is critical to morphogenesis, just as they seem to be during division of animal cells. In advanced green plants, intercalary expansion driven by turgor is controlled by MTs, which in conjunction with actin, may act as stress detectors, thereby affecting the plane of division (a response clearly evident after wounding of tissue). The PPB might be one manifestation of this strain detection apparatus.
Cervical cancer detection by time-resolved spectra of blood components

Abstract. Fluorescence spectral techniques are very sensitive, and hence they are gaining importance in cancer detection. The biomarkers indicative of cancer could be identified and quantified by spectral or time domain fluorescence spectroscopy. The results of an investigation of time-resolved spectra of cellular components of blood obtained from cervical cancer patients and normal controls are given. The cancer indicative biomarker in this paper is porphyrin; it has a fluorescence decay time of 60% more in samples of cancer patients than those of normal controls. Based on such measurements, a randomized set comprising samples from cancer patients and controls (N=27 in total) could be classified with sensitivity (92%) and specificity (86%).
Avian Fruit Removal: Effects of Fruit Variation, Crop Size, and Insect Damage.

Avian dispersal of seeds of the wild olive tree (Olea europaea var. sylvestris) was studied in Mediterranean shrubland, southern Spain. Fourteen species of small frugivorous birds in the genera Sylvia, Turdus, Sturnus, and Erithacus accounted for 97.4% of the fruits consumed by birds. The significance of each bird species as an Olea fruit consumer was closely related to its abundance in the area and was not associated with its dependence on the fruit for food; this resulted in a highly asymmetric interaction between the plant and its dispersers. Fruit production differed greatly between two consecutive seasons. During an extremely dry year most trees aborted their entire fruit crop just after flowering. During the 2nd yr, both flower production and fruit set increased, and this resulted in larger crops of ripe fruit. Most fruits that ripened (96.2% of the final-sized fruits) during the year of low fruit production were consumed by dispersers (X = 93.9%), and incidence of fruit-damaging agents was low (6.0%). During the 2nd yr, fruit loss to the two main fruit predators, Dacus oleae (Tephritidae) and Prays oleae (Yponomeutidae), increased (X = 27.1%, range 1.1-52.3%). A satiation process took place during this year since fruit production exceeded the energy demand of the disperser assemblage, and this increased the potential for fruit loss to insect frugivores. Fruit removal by dispersers decreased (X = 52.4%), but the increase in fecundity during the 2nd yr for most of the trees compensated for this difference and resulted in a greater absolute number of seeds removed. Most variation in ripe fruit removal by birds was attributed to the interaction of dispersal-related plant traits with insect frugivores that determine post-ripening fruit losses. The types of higher order interactions that result from the action of birds, the pulp-damaging fly, and the seed-eating moth larva may damp, or reverse, any selective effect of a single system component on plant traits related to seed dispersal.