Journal articles on the topic 'Encoding Mappings'
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1
Turer, Robert W., Theresa D. Zuckowsky, H. Jennifer Causey, and S. Trent Rosenbloom. "ICD-10-CM Crosswalks in the primary care setting: assessing reliability of the GEMs and reimbursement mappings." Journal of the American Medical Informatics Association 22, no. 2 (February 7, 2015): 417–25. http://dx.doi.org/10.1093/jamia/ocu028.
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Abstract Objective The general equivalence mappings (GEMs) and reimbursement mappings (RMs) facilitate translation between ICD-9-CM and ICD-10-CM. This study compared prospectively dual-encoded diagnoses assigned by professional coders with the GEMs/RMs in a clinical setting. Materials and Methods Professional coders manually encoded diagnoses from 100 primary care notes into both ICD-9-CM and ICD-10-CM. The investigators evaluated whether manual mappings were reproducible using the GEMs/RMs. Reproducible mappings with one ICD-9-CM and one ICD-10-CM code (“one-to-one”) were classified as exact or approximate using GEMs flags. Mismatches were characterized manually. Results Manual encodings were reproducible from the forward GEMs, backward GEMs, and RMs in 85.2%, 90.4%, and 88.1% of diagnoses, respectively. For one-to-one, reproducible mappings, 61% (forward) and 63% (backward) were approximate mappings compared to 85% and 95% in the GEMs as a whole. Mismatches between manual and GEMs encodings were due to differences in coder interpretation (11%–13%), subtle hierarchical differences (52%–55%), or unknown reasons (32%–35%). Discussion This study highlights inconsistencies between manual encoding and using the GEMs/RMs. The number of approximate mappings in our population compared to all one-to-one GEMs entries supports the notion that statistics describing the GEMs as a whole might not represent the most important mappings for each organization. The mismatch characteristics highlight the subtle differences between manual encoding and using the GEMs/RMs. Conclusion These results support the need for organizations to assess the GEMs and RMs in their own environment to avoid changes in reimbursement and longitudinal statistics.
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Fujiwara, Yusuke, Yoichi Miyawaki, and Yukiyasu Kamitani. "Modular Encoding and Decoding Models Derived from Bayesian Canonical Correlation Analysis." Neural Computation 25, no. 4 (April 2013): 979–1005. http://dx.doi.org/10.1162/neco_a_00423.
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Neural encoding and decoding provide perspectives for understanding neural representations of sensory inputs. Recent functional magnetic resonance imaging (fMRI) studies have succeeded in building prediction models for encoding and decoding numerous stimuli by representing a complex stimulus as a combination of simple elements. While arbitrary visual images were reconstructed using a modular model that combined the outputs of decoder modules for multiscale local image bases (elements), the shapes of the image bases were heuristically determined. In this work, we propose a method to establish mappings between the stimulus and the brain by automatically extracting modules from measured data. We develop a model based on Bayesian canonical correlation analysis, in which each module is modeled by a latent variable that relates a set of pixels in a visual image to a set of voxels in an fMRI activity pattern. The estimated mapping from a latent variable to pixels can be regarded as an image basis. We show that the model estimates a modular representation with spatially localized multiscale image bases. Further, using the estimated mappings, we derive encoding and decoding models that produce accurate predictions for brain activity and stimulus images. Our approach thus provides a novel means of revealing neural representations of stimuli by automatically extracting modules, which can be used to generate effective prediction models for encoding and decoding.
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Zhao, Weijie, and Xuechen Chen. "Zero-Delay Joint Source Channel Coding for a Bivariate Gaussian Source over the Broadcast Channel with One-Bit ADC Front Ends." Entropy 23, no. 12 (December 14, 2021): 1679. http://dx.doi.org/10.3390/e23121679.
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In this work, we consider the zero-delay transmission of bivariate Gaussian sources over a Gaussian broadcast channel with one-bit analog-to-digital converter (ADC) front ends. An outer bound on the conditional distortion region is derived. Focusing on the minimization of the average distortion, two types of methods are proposed to design nonparametric mappings. The first one is based on the joint optimization between the encoder and decoder with the use of an iterative algorithm. In the second method, we derive the necessary conditions to develop the optimal encoder numerically. Using these necessary conditions, an algorithm based on gradient descent search is designed. Subsequently, the characteristics of the optimized encoding mapping structure are discussed, and inspired by which, several parametric mappings are proposed. Numerical results show that the proposed parametric mappings outperform the uncoded scheme and previous parametric mappings for broadcast channels with infinite resolution ADC front ends. The nonparametric mappings succeed in outperforming the parametric mappings. The causes for the differences between the performances of two nonparametric mappings are analyzed. The average distortions of the parametric and nonparametric mappings proposed here are close to the bound for the cases with one-bit ADC front ends in low channel signal-to-noise ratio regions.
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Caso, Gregory, and C. C. Jay Kuo. "Multiresolution Analysis of Fractal Image Compression." Fractals 05, supp01 (April 1997): 215–29. http://dx.doi.org/10.1142/s0218348x97000772.
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In this research, we perform a multiresolution analysis of the mappings used in fractal image compression. We derive the transform-domain structure of the mappings and demonstrate a close connection between fractal image compression and wavelet transform coding using the Haar basis. We show that under certain conditions, the mappings correspond to a hierarchy of affine mappings between the subbands of the transformed image. Our analysis provides new insights into the mechanism underlying fractal image compression, leads to a new non-iterative transform-domain decoding algorithm, and suggests a new transform-domain encoding method with extensions to wavelets other than the Haar transform.
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Garner, Kelly G., Natasha Matthews, Roger W. Remington, and Paul E. Dux. "Transferability of Training Benefits Differs across Neural Events: Evidence from ERPs." Journal of Cognitive Neuroscience 27, no. 10 (October 2015): 2079–94. http://dx.doi.org/10.1162/jocn_a_00833.
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Humans can show striking capacity limitations in sensorimotor processing. Fortunately, these limitations can be attenuated with training. However, less fortunately, training benefits often remain limited to trained tasks. Recent behavioral observations suggest that the extent to which training transfers may depend on the specific stage of information processing that is being executed. Training benefits for a task that taps the consolidation of sensory information (sensory encoding) transfer to new stimulus–response mappings, whereas benefits for selecting an appropriate action (decision-making/response selection) remain specific to the trained mappings. Therefore, training may have dissociable influences on the neural events underlying subsequent sensorimotor processing stages. Here, we used EEG to investigate this possibility. In a pretraining baseline session, participants completed two four-alternative-choice response time tasks, presented both as a single task and as part of a dual task (with another task). The training group completed a further 3,000 training trials on one of the four-alternative-choice tasks. Hence, one task became trained, whereas the other remained untrained. At test, a negative-going component that is sensitive to sensory-encoding demands (N2) showed increased amplitudes and reduced latencies for trained and untrained mappings relative to a no-train control group. In contrast, the onset of the stimulus-locked lateralized readiness potential, a component that reflects the activation of motor plans, was reduced only for tasks that employed trained stimulus–response mappings, relative to untrained stimulus–response mappings and controls. Collectively, these results show that training benefits are dissociable for the brain events that reflect distinct sensorimotor processing stages.
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Nord, Alexander J., and Travis J. Wheeler. "Mirage2’s high-quality spliced protein-to-genome mappings produce accurate multiple-sequence alignments of isoforms." PLOS ONE 18, no. 5 (May 8, 2023): e0285225. http://dx.doi.org/10.1371/journal.pone.0285225.
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The organization of homologous protein sequences into multiple sequence alignments (MSAs) is a cornerstone of modern analysis of proteins. Recent focus on the importance of alternatively-spliced isoforms in disease and cell biology has highlighted the need for MSA software that can appropriately account for isoforms and the exon-length insertions or deletions that isoforms may have relative to each other. We previously developed Mirage, a software package for generating MSAs for isoforms spanning multiple species. Here, we present Mirage2, which retains the fundamental algorithms of the original Mirage implementation while providing substantially improved translated mapping and improving several aspects of usability. We demonstrate that Mirage2 is highly effective at mapping proteins to their encoding exons, and that these protein-genome mappings lead to extremely accurate intron-aware alignments. Additionally, Mirage2 implements a number of engineering improvements that simplify installation and use.
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Steiner, Erich. "Ideational grammatical metaphor." Languages in Contrast 4, no. 1 (April 14, 2004): 137–64. http://dx.doi.org/10.1075/lic.4.1.07ste.
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In this paper I want to explore the systemic-functional notion of ‘grammatical metaphor’ from a cross-linguistic perspective. After a brief introduction to the concept of ‘grammatical metaphor’, I shall discuss the distinction between ‘congruent’ and ‘metaphorical’ encodings of meaning, as well as the distinction between rankshift, transcategorization, and grammatical metaphor as semogenic resources (Section 1). In a second section, I shall then focus on ideational grammatical metaphors in English and German and revisit the notion of direct vs. indirect mapping of experiential and logical semantics onto lexicogrammar (Section 2). It will be argued that ‘directness of encoding’ within one language can be defined with the help of the concept of ‘transparency’ or ‘motivation’ of encoding between levels. Across and between languages, however, the notion of ‘directness’ either has to be seen from the perspective of one of the languages involved, or from the perspective of a generalized semantics and grammar. In Section 3, I shall then explore the question of the experiential vs. logical encoding of semantic categories across languages, and of how this relates to metaphoricity. I shall exemplify and discuss the fact that in cross-linguistic analyses, one cannot consider any one of a given set of experiential or logical encodings of some unit of meaning as ‘congruent’ or ‘direct’, as long as one does not have a cross-linguistic semantics to establish ‘motivation’ and ‘transparentness’ on. It will also be argued that some of the differences in texts across languages as to what counts as ‘congruent’ can be predicted from comparisons between the language-specific grammatical systems involved. Other differences, however, seem to rely heavily on registerial influences and cultural factors. In Section 4, then, I shall inquire into the question of whether and precisely in what sense we can speak of two different types of grammatical metaphor, dependent on whether they involve a relocation in rank or a mere re-arrangement of mappings of semantic and lexicogrammatical functions. These types of metaphor, it will be argued, have different implications for the metaphoricity of the clause as a whole, as well as for the ‘density’ of the packaging of meaning.
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Pearson, Toni S., John W. Krakauer, and Pietro Mazzoni. "Learning Not to Generalize: Modular Adaptation of Visuomotor Gain." Journal of Neurophysiology 103, no. 6 (June 2010): 2938–52. http://dx.doi.org/10.1152/jn.01089.2009.
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When a new sensorimotor mapping is learned through practice, learning commonly transfers to unpracticed regions of task space, that is, generalization ensues. Does generalization reflect fixed properties of movement representations in the nervous system and thereby limit what visuomotor mappings can and cannot be learned? Or does what needs to be learned determine the shape of generalization? We used the broad generalization properties of visuomotor gain adaptation to address these questions. Adaptation to a single gain for reaching movements is known to generalize broadly across movement directions. By training subjects on two different gains in two directions, we set up a potential conflict between generalization patterns: if generalization of gain adaptation indicates fixed properties of movement amplitude encoding, then learning two different gains in different directions should not be possible. Conversely, if generalization is flexible, then it should be possible to learn two gains. We found that subjects were able to learn two gains simultaneously, although more slowly than when they adapted to a single gain. Analysis of the resulting double-gain generalization patterns, however, unexpectedly revealed that generalization around each training direction did not arise de novo, but could be explained by a weighted combination of single-gain generalization patterns, in which the weighting takes into account the relative angular separation between training directions. Our findings therefore demonstrate that the mappings to each training target can be fully learned through reweighting of single-gain generalization patterns and not through a categorical alteration of these functions. These results are consistent with a modular decomposition approach to visuomotor adaptation, in which a complex mapping results from a combination of simpler mappings in a “mixture-of-experts” architecture.
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Li, Baojun, Lei Yang, Hui Jiang, Weixue Sun, and Ping Hu. "Concurrent editing of automotive styling and structure with wireframe-pair." Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering 231, no. 6 (November 13, 2016): 828–41. http://dx.doi.org/10.1177/0954407016669274.
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A constant demand in engineering design is to couple aesthetics and functionality of design. In this paper, a method is proposed to rapidly update the structural analysis models given the modifications made in the styling/packaging designs, forming a concurrent mechanism for developing the automotive styling and body structure. The seemingly disparate domains are represented by and thus coupled through a pair of wireframes. A joint mapping based on the hard points in packaging and a part mapping encoding local influences between wireframes are established. The deformation transfer from one of the wireframes to the other is solved as an optimization with constraints obtained from the two mappings. Finally, the finite element mesh model is adapted in accordance with the deformed structural wireframe, using a mesh morphing method based on the free-form deformation technique. Numerical results validate the proposed method and demonstrate its effectiveness.
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Hoggan, Eve. "Crossmodal Audio and Tactile Interaction with Mobile Touchscreens." International Journal of Mobile Human Computer Interaction 2, no. 4 (October 2010): 29–44. http://dx.doi.org/10.4018/jmhci.2010100102.
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This article asserts that using crossmodal auditory and tactile interaction can aid mobile touchscreen users in accessing data non-visually and, by providing a choice of modalities, can help to overcome problems that occur in different mobile situations where one modality may be less suitable than another (Hoggan, 2010). By encoding data using the crossmodal parameters of audio and vibration, users can learn mappings and translate information between both modalities. In this regard, data may be presented to the most appropriate modality given the situation and surrounding environment.
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Gardner, Brian, Ioana Sporea, and André Grüning. "Learning Spatiotemporally Encoded Pattern Transformations in Structured Spiking Neural Networks." Neural Computation 27, no. 12 (December 2015): 2548–86. http://dx.doi.org/10.1162/neco_a_00790.
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Information encoding in the nervous system is supported through the precise spike timings of neurons; however, an understanding of the underlying processes by which such representations are formed in the first place remains an open question. Here we examine how multilayered networks of spiking neurons can learn to encode for input patterns using a fully temporal coding scheme. To this end, we introduce a new supervised learning rule, MultilayerSpiker, that can train spiking networks containing hidden layer neurons to perform transformations between spatiotemporal input and output spike patterns. The performance of the proposed learning rule is demonstrated in terms of the number of pattern mappings it can learn, the complexity of network structures it can be used on, and its classification accuracy when using multispike-based encodings. In particular, the learning rule displays robustness against input noise and can generalize well on an example data set. Our approach contributes to both a systematic understanding of how computations might take place in the nervous system and a learning rule that displays strong technical capability.
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Li, Hongming, Lilai Zhang, Hao Cao, and Yirui Wu. "Hash Based DNA Computing Algorithm for Image Encryption." Applied Sciences 13, no. 14 (July 23, 2023): 8509. http://dx.doi.org/10.3390/app13148509.
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Deoxyribonucleic Acid (DNA) computing has demonstrated great potential in data encryption due to its capability of parallel computation, minimal storage requirement, and unbreakable cryptography. Focusing on high-dimensional image data for encryption with DNA computing, we propose a novel hash encoding-based DNA computing algorithm, which consists of a DNA hash encoding module and content-aware encrypting module. Inspired by the significant properties of the hash function, we build a quantity of hash mappings from image pixels to DNA computing bases, properly integrating the advantages of the hash function and DNA computing to boost performance. Considering the correlation relationship of pixels and patches for modeling, a content-aware encrypting module is proposed to reorganize the image data structure, resisting the crack with non-linear and high dimensional complexity originating from the correlation relationship. The experimental results suggest that the proposed method performs better than most comparative methods in key space, histogram analysis, pixel correlation, information entropy, and sensitivity measurements.
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Sakk, Eric, and Ayanna Alexander. "On the Variability of Neural Network Classification Measures in the Protein Secondary Structure Prediction Problem." Applied Computational Intelligence and Soft Computing 2013 (2013): 1–9. http://dx.doi.org/10.1155/2013/794350.
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We revisit the protein secondary structure prediction problem using linear and backpropagation neural network architectures commonly applied in the literature. In this context, neural network mappings are constructed between protein training set sequences and their assigned structure classes in order to analyze the class membership of test data and associated measures of significance. We present numerical results demonstrating that classifier performance measures can vary significantly depending upon the classifier architecture and the structure class encoding technique. Furthermore, an analytic formulation is introduced in order to substantiate the observed numerical data. Finally, we analyze and discuss the ability of the neural network to accurately model fundamental attributes of protein secondary structure.
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Christen, Markus, Peter Brugger, and Sara Irina Fabrikant. "Susceptibility of domain experts to color manipulation indicate a need for design principles in data visualization." PLOS ONE 16, no. 2 (February 4, 2021): e0246479. http://dx.doi.org/10.1371/journal.pone.0246479.
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Color is key for the visual encoding of data, yet its use reportedly affects decision making in important ways. We examined the impact of various popular color schemes on experts’ and lay peoples’ map-based decisions in two, geography and neuroscience, scenarios, in an online visualization experiment. We found that changes in color mappings influence domain experts, especially neuroimaging experts, more in their decision-making than novices. Geographic visualization experts exhibited more trust in the unfavorable rainbow color scale than would have been predicted by their suitability ratings and their training, which renders them sensitive to scale appropriateness. Our empirical results make a strong call for increasing scientists’ awareness for and training in perceptually salient and cognitively informed design principles in data visualization.
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Ricci-Tam, C., I. Ben-Zion, J. Wang, J. Palme, A. Li, Y. Savir, and M. Springer. "Decoupling transcription factor expression and activity enables dimmer switch gene regulation." Science 372, no. 6539 (April 15, 2021): 292–95. http://dx.doi.org/10.1126/science.aba7582.
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Gene-regulatory networks achieve complex mappings of inputs to outputs through mechanisms that are poorly understood. We found that in the galactose-responsive pathway in Saccharomyces cerevisiae, the decision to activate the transcription of genes encoding pathway components is controlled independently from the expression level, resulting in behavior resembling that of a mechanical dimmer switch. This was not a direct result of chromatin regulation or combinatorial control at galactose-responsive promoters; rather, this behavior was achieved by hierarchical regulation of the expression and activity of a single transcription factor. Hierarchical regulation is ubiquitous, and thus dimmer switch regulation is likely a key feature of many biological systems. Dimmer switch gene regulation may allow cells to fine-tune their responses to multi-input environments on both physiological and evolutionary time scales.
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Lv, Ning, Zhen Han, Chen Chen, Yijia Feng, Tao Su, Sotirios Goudos, and Shaohua Wan. "Encoding Spectral-Spatial Features for Hyperspectral Image Classification in the Satellite Internet of Things System." Remote Sensing 13, no. 18 (September 7, 2021): 3561. http://dx.doi.org/10.3390/rs13183561.
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Hyperspectral image classification is essential for satellite Internet of Things (IoT) to build a large scale land-cover surveillance system. After acquiring real-time land-cover information, the edge of the network transmits all the hyperspectral images by satellites with low-latency and high-efficiency to the cloud computing center, which are provided by satellite IoT. A gigantic amount of remote sensing data bring challenges to the storage and processing capacity of traditional satellite systems. When hyperspectral images are used in annotation of land-cover application, data dimension reduction for classifier efficiency often leads to the decrease of classifier accuracy, especially the region to be annotated consists of natural landform and artificial structure. This paper proposes encoding spectral-spatial features for hyperspectral image classification in the satellite Internet of Things system to extract features effectively, namely attribute profile stacked autoencoder (AP-SAE). Firstly, extended morphology attribute profiles EMAP is used to obtain spatial features of different attribute scales. Secondly, AP-SAE is used to extract spectral features with similar spatial attributes. In this stage the program can learn feature mappings, on which the pixels from the same land-cover class are mapped as closely as possible and the pixels from different land-cover categories are separated by a large margin. Finally, the program trains an effective classifier by using the network of the AP-SAE. Experimental results on three widely-used hyperspectral image (HSI) datasets and comprehensive comparisons with existing methods demonstrate that our proposed method can be used effectively in hyperspectral image classification.
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TOPPAN, F. "N = 1, 2 SUPER-NLS HIERARCHIES AS SUPER-KP COSET REDUCTIONS." International Journal of Modern Physics A 10, no. 06 (March 10, 1995): 895–922. http://dx.doi.org/10.1142/s0217751x95000449.
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We define consistent finite-superfield reductions of the N = 1, 2 super-KP hierarchies via the coset approach we have already developed for reducing the bosonic KP hierarchy [generating for example the NLS hierarchy from the [Formula: see text] coset]. We work in a manifestly supersymmetric framework and illustrate our method by treating explicitly the N = 1, 2 super-NLS hierarchies. With respect to the bosonic case the ordinary covariant derivative is now replaced by a spinorial one which contains a spin-[Formula: see text] superfield. Each coset reduction is associated with a rational super-[Formula: see text] algebra encoding a nonlinear super-[Formula: see text]-algebra structure. In the N = 2 case two conjugate sets of super-Lax operators, equations of motion and infinite Hamiltonians in involution are derived. Modified hierarchies are obtained from the original ones via free-field mappings [just as an m-NLS equation arises from representing the [Formula: see text] algebra through the classical Wakimoto free fields].
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Pomarico, Domenico, Annarita Fanizzi, Nicola Amoroso, Roberto Bellotti, Albino Biafora, Samantha Bove, Vittorio Didonna, et al. "A Proposal of Quantum-Inspired Machine Learning for Medical Purposes: An Application Case." Mathematics 9, no. 4 (February 19, 2021): 410. http://dx.doi.org/10.3390/math9040410.
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Learning tasks are implemented via mappings of the sampled data set, including both the classical and the quantum framework. Biomedical data characterizing complex diseases such as cancer typically require an algorithmic support for clinical decisions, especially for early stage tumors that typify breast cancer patients, which are still controllable in a therapeutic and surgical way. Our case study consists of the prediction during the pre-operative stage of lymph node metastasis in breast cancer patients resulting in a negative diagnosis after clinical and radiological exams. The classifier adopted to establish a baseline is characterized by the result invariance for the order permutation of the input features, and it exploits stratifications in the training procedure. The quantum one mimics support vector machine mapping in a high-dimensional feature space, yielded by encoding into qubits, while being characterized by complexity. Feature selection is exploited to study the performances associated with a low number of features, thus implemented in a feasible time. Wide variations in sensitivity and specificity are observed in the selected optimal classifiers during cross-validations for both classification system types, with an easier detection of negative or positive cases depending on the choice between the two training schemes. Clinical practice is still far from being reached, even if the flexible structure of quantum-inspired classifier circuits guarantees further developments to rule interactions among features: this preliminary study is solely intended to provide an overview of the particular tree tensor network scheme in a simplified version adopting just product states, as well as to introduce typical machine learning procedures consisting of feature selection and classifier performance evaluation.
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Dai, Xili, Shengbang Tong, Mingyang Li, Ziyang Wu, Michael Psenka, Kwan Ho Ryan Chan, Pengyuan Zhai, et al. "CTRL: Closed-Loop Transcription to an LDR via Minimaxing Rate Reduction." Entropy 24, no. 4 (March 25, 2022): 456. http://dx.doi.org/10.3390/e24040456.
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This work proposes a new computational framework for learning a structured generative model for real-world datasets. In particular, we propose to learn a Closed-loop Transcriptionbetween a multi-class, multi-dimensional data distribution and a Linear discriminative representation (CTRL) in the feature space that consists of multiple independent multi-dimensional linear subspaces. In particular, we argue that the optimal encoding and decoding mappings sought can be formulated as a two-player minimax game between the encoder and decoderfor the learned representation. A natural utility function for this game is the so-called rate reduction, a simple information-theoretic measure for distances between mixtures of subspace-like Gaussians in the feature space. Our formulation draws inspiration from closed-loop error feedback from control systems and avoids expensive evaluating and minimizing of approximated distances between arbitrary distributions in either the data space or the feature space. To a large extent, this new formulation unifies the concepts and benefits of Auto-Encoding and GAN and naturally extends them to the settings of learning a both discriminative and generative representation for multi-class and multi-dimensional real-world data. Our extensive experiments on many benchmark imagery datasets demonstrate tremendous potential of this new closed-loop formulation: under fair comparison, visual quality of the learned decoder and classification performance of the encoder is competitive and arguably better than existing methods based on GAN, VAE, or a combination of both. Unlike existing generative models, the so-learned features of the multiple classes are structured instead of hidden: different classes are explicitly mapped onto corresponding independent principal subspaces in the feature space, and diverse visual attributes within each class are modeled by the independent principal components within each subspace.
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Wu, Jifang, Jianghua Lv, Haoming Guo, and Shilong Ma. "DAEOM: A Deep Attentional Embedding Approach for Biomedical Ontology Matching." Applied Sciences 10, no. 21 (November 8, 2020): 7909. http://dx.doi.org/10.3390/app10217909.
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Ontology Matching (OM) is performed to find semantic correspondences between the entity elements of different ontologies to enable semantic integration, reuse, and interoperability. Representation learning techniques have been introduced to the field of OM with the development of deep learning. However, there still exist two limitations. Firstly, these methods only focus on the terminological-based features to learn word vectors for discovering mappings, ignoring the network structure of ontology. Secondly, the final alignment threshold is usually determined manually within these methods. It is difficult for an expert to adjust the threshold value and even more so for a non-expert user. To address these issues, we propose an alternative ontology matching framework called Deep Attentional Embedded Ontology Matching (DAEOM), which models the matching process by embedding techniques with jointly encoding ontology terminological description and network structure. We propose a novel inter-intra negative sampling skill tailored for the structural relations asserted in ontologies, and further improve our iterative final alignment method by introducing an automatic adjustment of the final alignment threshold. The preliminary result on real-world biomedical ontologies indicates that DAEOM is competitive with several OAEI top-ranked systems in terms of F-measure.
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Goswami, Usha. "A Neural Basis for Phonological Awareness? An Oscillatory Temporal-Sampling Perspective." Current Directions in Psychological Science 27, no. 1 (December 14, 2017): 56–63. http://dx.doi.org/10.1177/0963721417727520.
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Individual differences in phonological awareness, or speech-sound awareness, between children predict reading and spelling development across languages. Recent advances in our understanding of the neural basis of speech encoding suggest one possible sensory and neural basis for these individual differences. This article describes an oscillatory theoretical perspective based on sampling of the speech stream by networks of cells that vary in excitability at different temporal rates. These variations in neural excitability (oscillations) may align to similar energy variations (such as amplitude modulations, AMs) in speech, helping to encode the signal. Indeed, cell networks in auditory cortex form an oscillatory hierarchy, which mirrors an AM hierarchy found in rhythmic speech. Mappings between these hierarchies may support parsing of the speech signal into phonological units. Oscillations at approximately 2 Hz may help identify stressed syllables, used to convey meaning in all languages, while oscillations at approximately 5 Hz may help identify syllables. Behavioral research suggests that the rhythmic patterning of stressed syllables may provide an acoustic “skeleton” for phonological development across languages. As well as helping to explain individual differences, an oscillatory framework offers new targets for improving children’s phonological development, for example, via multimodal rhythmic activities.
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Sánchez-Fibla, Martí, Sébastien Forestier, Clément Moulin-Frier, Jordi-Ysard Puigbò, and Paul FMJ Verschure. "From motor to visually guided bimanual affordance learning." Adaptive Behavior 28, no. 2 (July 2, 2019): 63–78. http://dx.doi.org/10.1177/1059712319855836.
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The mechanisms of how the brain orchestrates multi-limb joint action have yet to be elucidated and few computational sensorimotor (SM) learning approaches have dealt with the problem of acquiring bimanual affordances. We propose a series of bidirectional (forward/inverse) SM maps and its associated learning processes that generalize from uni- to bimanual interaction (and affordances) naturally, reinforcing the motor equivalence property. The SM maps range from a SM nature to a solely sensory one: full body control, delta SM control (through small action changes), delta sensory co-variation (how body-related perceptual cues covariate with object-related ones). We make several contributions on how these SM maps are learned: (1) Context and Behavior-Based Babbling: generalizing goal babbling to the interleaving of absolute and local goals including guidance of reflexive behaviors; (2) Event-Based Learning: learning steps are driven by visual, haptic events; and (3) Affordance Gradients: the vectorial field gradients in which an object can be manipulated. Our modeling of bimanual affordances is in line with current robotic research in forward visuomotor mappings and visual servoing, enforces the motor equivalence property, and is also consistent with neurophysiological findings like the multiplicative encoding scheme.
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Bourguignon, Nicolas J., Senne Braem, Egbert Hartstra, Jan De Houwer, and Marcel Brass. "Encoding of Novel Verbal Instructions for Prospective Action in the Lateral Prefrontal Cortex: Evidence from Univariate and Multivariate Functional Magnetic Resonance Imaging Analysis." Journal of Cognitive Neuroscience 30, no. 8 (August 2018): 1170–84. http://dx.doi.org/10.1162/jocn_a_01270.
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Verbal instructions are central to humans' capacity to learn new behaviors with minimal training, but the neurocognitive mechanisms involved in verbally instructed behaviors remain puzzling. Recent functional magnetic resonance imaging (fMRI) evidence suggests that the right middle frontal gyrus and dorsal premotor cortex (rMFG-dPMC) supports the translation of symbolic stimulus–response mappings into sensorimotor representations. Here, we set out to (1) replicate this finding, (2) investigate whether this region's involvement is specific to novel (vs. trained) instructions, and (3) study whether rMFG-dPMC also shows differences in its (voxel) pattern response indicative of general cognitive processes of instruction implementation. Participants were shown instructions, which they either had to perform later or merely memorize. Orthogonal to this manipulation, the instructions were either entirely novel or had been trained before the fMRI session. Results replicate higher rMFG-dPMC activation levels during instruction implementation versus memorization and show how this difference is restricted to novel, but not trained, instruction presentations. Pattern similarity analyses at the voxel level further reveal more consistent neural pattern responses in rMFG-dPMC during the implementation of novel versus trained instructions. In fact, this more consistent neural pattern response seemed to be specific to the first instruction presentation and disappeared after the instruction had been applied once. These results further support a role of rMFG-dPMC in the implementation of novel task instructions and highlight potentially important differences in studying this region's gross activation levels versus (the consistency of) its response patterns.
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Hourrane, Oumaima, and El Habib Benlahmar. "Graph transformer for cross-lingual plagiarism detection." IAES International Journal of Artificial Intelligence (IJ-AI) 11, no. 3 (September 1, 2022): 905. http://dx.doi.org/10.11591/ijai.v11.i3.pp905-915.
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<span lang="EN-US">The existence of vast amounts of multilingual textual data on the internet leads to cross-lingual plagiarism which becomes a serious issue in different fields such as education, science, and literature. Current cross-lingual plagiarism detection approaches usually employ syntactic and lexical properties, external machine translation systems, or finding similarities within a multilingual set of text documents. However, most of these methods are conceived for literal plagiarism such as copy and paste, and their performance is diminished when handling complex cases of plagiarism including paraphrasing. In this paper, we propose a new graph-based approach that represents text passages in different languages using knowledge graphs. We put forward a new graph structure modeling method based on the Transformer architecture that employs precise relation encoding and delivers a more efficient way for global graph representation. The mappings between the graphs are learned both in semi-supervised and unsupervised training mechanisms. The results of our experiments in Arabic–English, French–English, and Spanish–English plagiarism detection show that our graph transformer method surpasses the state-of-the-art cross-lingual plagiarism detection approaches with and without paraphrasing cases, and provides further insights on the use of knowledge graphs on a language-independent model.</span>
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Perikova, Ekaterina I., Margarita G. Filippova, Daria S. Gnedykh, Daria N. Makarova, Olga V. Shcherbakova, and Yury Shtyrov. "Имплицитное и эксплицитное усвоение новых слов: схожая эффективность, но разные механизмы?" Психология. Журнал Высшей школы экономики 20, no. 2 (June 30, 2023): 370–85. http://dx.doi.org/10.17323/1813-8918-2023-2-370-385.
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Two language learning strategies have been described as common in both children and adults: fast mapping (FM), which promotes learning from context, and explicit encoding (EE), which is provided through direct instruction. Pre vious functional neuroimaging studies in adult learners have suggested differential neural mechanisms underlying these two major cognitive strategies, with some limited evidence in support of such differences also found in behavioural experiments. Nevertheless, the exact nature of these differences remains underinvestigated. Our goal was to explore putative differential effects of EE and FM strategies on the acquisition of novel words, with a focus on scrutinising the quality of recognition of newly learnt items. In two experiments, participants (total sample size = 82) learned 18 novel words presented ten times each in a word-picture association paradigm using EE and FM conditions. Learning outcomes were assessed immediately after the training using a recognition task. In both experiments, we found no differences in either the accuracy or the reaction time of word recognition between FM and EE conditions, which suggests similar behavioural efficiency of both strategies. However, we found a negative correlation between reaction time and response accuracy in recognising the words learned through EE, with no similar effects for FM, which indicates qualitative differences in underlying memory traces formed via these two acquisition modes. These results can be seen to imply that people tend to use information acquired through EE more confidently than that acquired through FM.
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Komosiński, Maciej, and Adam Rotaru-Varga. "Comparison of Different Genotype Encodings for Simulated Three-Dimensional Agents." Artificial Life 7, no. 4 (October 2001): 395–418. http://dx.doi.org/10.1162/106454601317297022.
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We analyze the effect of different genetic encodings used for evolving three-dimensional agents with physical morphologies. The complex phenotypes used in such systems often require nontrivial encodings. Different encodings used in Framsticks—a system for evolving three-dimensional agents—are presented. These include a low-level direct mapping and two higher-level encodings: one recurrent and one developmental. Quantitative results are presented from three simple optimization tasks (passive height, active height, and locomotion speed). The low-level encoding produced solutions of lower fitness than the two higher-level encodings under similar conditions. Results from recurrent and developmental encodings had similar fitness values but displayed qualitative differences. Desirable advantages and some drawbacks of more complex encodings are established.
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van Vugt, Floris T., and David J. Ostry. "The Structure and Acquisition of Sensorimotor Maps." Journal of Cognitive Neuroscience 30, no. 3 (March 2018): 290–306. http://dx.doi.org/10.1162/jocn_a_01204.
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One of the puzzles of learning to talk or play a musical instrument is how we learn which movement produces a particular sound: an audiomotor map. Existing research has used mappings that are already well learned such as controlling a cursor using a computer mouse. By contrast, the acquisition of novel sensorimotor maps was studied by having participants learn arm movements to auditory targets. These sounds did not come from different directions but, like speech, were only distinguished by their frequencies. It is shown that learning involves forming not one but two maps: a point map connecting sensory targets with motor commands and an error map linking sensory errors to motor corrections. Learning a point map is possible even when targets never repeat. Thus, although participants make errors, there is no opportunity to correct them because the target is different on every trial, and therefore learning cannot be driven by error correction. Furthermore, when the opportunity for error correction is provided, it is seen that acquiring error correction is itself a learning process that changes over time and results in an error map. In principle, the error map could be derived from the point map, but instead, these two maps are independently acquired and jointly enable sensorimotor control and learning. A computational model shows that this dual encoding is optimal and simulations based on this architecture predict that learning the two maps results in performance improvements comparable with those observed empirically.
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Petrides, Michael. "Lateral prefrontal cortex: architectonic and functional organization." Philosophical Transactions of the Royal Society B: Biological Sciences 360, no. 1456 (April 29, 2005): 781–95. http://dx.doi.org/10.1098/rstb.2005.1631.
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A comparison of the architecture of the human prefrontal cortex with that of the macaque monkey showed a very similar architectonic organization in these two primate species. There is no doubt that the prefrontal cortical areas of the human brain have undergone considerable development, but it is equally clear that the basic architectonic organization is the same in the two species. Thus, a comparative approach to the study of the functional organization of the primate prefrontal cortex is more likely to reveal the essential aspects of the various complex control processes that are the domain of frontal function. The lateral frontal cortex appears to be functionally organized along both a rostral–caudal axis and a dorsal–ventral axis. The most caudal frontal region, the motor region on the precentral gyrus, is involved in fine motor control and direct sensorimotor mappings, whereas the caudal lateral prefrontal region is involved in higher order control processes that regulate the selection among multiple competing responses and stimuli based on conditional operations. Further rostrally, the mid-lateral prefrontal region plays an even more abstract role in cognitive control. The mid-lateral prefrontal region is itself organized along a dorsal–ventral axis of organization, with the mid-dorsolateral prefrontal cortex being involved in the monitoring of information in working memory and the mid-ventrolateral prefrontal region being involved in active judgments on information held in posterior cortical association regions that are necessary for active retrieval and encoding of information.
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Frey, Katharina, and Boas Pucker. "Animal, Fungi, and Plant Genome Sequences Harbor Different Non-Canonical Splice Sites." Cells 9, no. 2 (February 18, 2020): 458. http://dx.doi.org/10.3390/cells9020458.
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Most protein-encoding genes in eukaryotes contain introns, which are interwoven with exons. Introns need to be removed from initial transcripts in order to generate the final messenger RNA (mRNA), which can be translated into an amino acid sequence. Precise excision of introns by the spliceosome requires conserved dinucleotides, which mark the splice sites. However, there are variations of the highly conserved combination of GT at the 5′ end and AG at the 3′ end of an intron in the genome. GC-AG and AT-AC are two major non-canonical splice site combinations, which have been known for years. Recently, various minor non-canonical splice site combinations were detected with numerous dinucleotide permutations. Here, we expand systematic investigations of non-canonical splice site combinations in plants across eukaryotes by analyzing fungal and animal genome sequences. Comparisons of splice site combinations between these three kingdoms revealed several differences, such as an apparently increased CT-AC frequency in fungal genome sequences. Canonical GT-AG splice site combinations in antisense transcripts are a likely explanation for this observation, thus indicating annotation errors. In addition, high numbers of GA-AG splice site combinations were observed in Eurytemora affinis and Oikopleura dioica. A variant in one U1 small nuclear RNA (snRNA) isoform might allow the recognition of GA as a 5′ splice site. In depth investigation of splice site usage based on RNA-Seq read mappings indicates a generally higher flexibility of the 3′ splice site compared to the 5′ splice site across animals, fungi, and plants.
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Gotsoulia, Voula. "Formalization of linking information in the FrameNet lexicon." Constructions and Frames 4, no. 2 (December 31, 2012): 103–51. http://dx.doi.org/10.1075/cf.4.2.01got.
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The paper presents a novel approach to formalization of linking information in the FrameNet lexicon and to acquisition of a principled syntax-semantics interface, suitable for generalizing over combinatorial properties (valences) of predicators. Focusing on verbs that denote ‘notions’, it adopts an entailment-based view of the concept of semantic role, proposing representations of verbal arguments based on semantically primitive, grammatically relevant properties, entailed by the meaning of predicators (lexical entailments). Such generic meaning components abstract over various semantic relations which humans tend to express systematically through language. A limited set of prototypical role-like concepts can be used for modeling the linking properties of a wide range of verbs, in a well-ordered fashion. In a preliminary study, frame-semantic representations of a set of notion verbs are mapped onto lexical entailment representations, in a portion of the FrameNet corpora. From the annotated data set, associations of semantic and grammatical categories are extracted and are formally rendered in entailment-based classes called Lexicalization Types (L-Types). L-Types are specified in terms of combinations of entailed properties, encoding distinctive predicate-argument structure patterns. A small number of L-Types is shown to readily abstract over the valence patterns of verbs classified in a variety of FrameNet frames. The latter are not systematically connected for purposes of linking. Valence generalizations in the FrameNet lexicon are acquired through appropriate frame-to-frame relations forming the frame hierarchy. L-Types can be represented as abstract, non-lexicalized frames specifying linking constraints. Mappings between L-Types and more specific frames can be encoded by means of a new frame relation modeling the syntax-semantics interface. Such a relation would simplify the current picture of the frame hierarchy by essentially decoupling purely lexical semantic information from information pertaining to linking.
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Tong, Jiping, Zhengshu Han, and Aonan Han. "Genetic analysis and molecular mapping of Rp, a mutant gene encoding red pericarp in rice (Oryza sativa L.)." Czech Journal of Genetics and Plant Breeding 57, No. 2 (April 9, 2021): 51–57. http://dx.doi.org/10.17221/70/2020-cjgpb.
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Coloured rice has pigments deposited in the grain pericarp; red rice is the most common type of coloured rice. Red rice is rich in essential nutrients and has been grown and consumed in China for a long time. In this study, we report the genetic characterisation and preliminary molecular mapping of a mutant gene encoding red pericarp in rice (Oryza sativa L.). To analyse the genetic basis of the red pericarp mutant, a reciprocal cross between GER-3 (red pericarp, indica cv.) and 898 (white pericarp, indica cv.) was made. The genetic analysis results confirmed that there was only one dominant gene, temporarily designated Rp (Red pericarp) controlling the segregation of the red pericarp in the F<sub>2</sub> population. For the molecular mapping of Rp, an F<sub>2</sub> population derived from an inter-subspecific cross between Gene Engineering Rice-3 (GER-3) and C418 (japonica cv., white pericarp) was constructed. The genotype of the pericarp colour of the F<sub>2</sub> individuals in the mapping population was validated by progeny testing of the F<sub>2:3</sub> families. Simple sequence repeat (SSR) markers and the bulked segregation analysis (BSA) method were used; Rp was mapped to the short arm of chromosome 7 between the SSR markers RM21182 and RM21268, with a genetic distance of 3.5 and 12.0 cM, respectively. In this paper, the potential origin of the red pericarp mutant gene Rp was also discussed.
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Peng, Weiping, Shuang Cui, and Cheng Song. "One-time-pad cipher algorithm based on confusion mapping and DNA storage technology." PLOS ONE 16, no. 1 (January 20, 2021): e0245506. http://dx.doi.org/10.1371/journal.pone.0245506.
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In order to solve the problems of low computational security in the encoding mapping and difficulty in practical operation of biological experiments in DNA-based one-time-pad cryptography, we proposed a one-time-pad cipher algorithm based on confusion mapping and DNA storage technology. In our constructed algorithm, the confusion mapping methods such as chaos map, encoding mapping, confusion encoding table and simulating biological operation process are used to increase the key space. Among them, the encoding mapping and the confusion encoding table provide the realization conditions for the transition of data and biological information. By selecting security parameters and confounding parameters, the algorithm realizes a more random dynamic encryption and decryption process than similar algorithms. In addition, the use of DNA storage technologies including DNA synthesis and high-throughput sequencing ensures a viable biological encryption process. Theoretical analysis and simulation experiments show that the algorithm provides both mathematical and biological security, which not only has the difficult advantage of cracking DNA biological experiments, but also provides relatively high computational security.
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Chengjia, Wu, Zhao Haiwu, and Shang Xiwu. "Octagonal Mapping Scheme for Panoramic Video Encoding." IEEE Transactions on Circuits and Systems for Video Technology 28, no. 9 (September 2018): 2402–6. http://dx.doi.org/10.1109/tcsvt.2018.2814074.
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Jankiewicz, Marcin, John C. Gore, and William A. Grissom. "Improved encoding pulses for Bloch–Siegert mapping." Journal of Magnetic Resonance 226 (January 2013): 79–87. http://dx.doi.org/10.1016/j.jmr.2012.11.004.
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Wang, Raymond, and Louis Kang. "Multiple bumps can enhance robustness to noise in continuous attractor networks." PLOS Computational Biology 18, no. 10 (October 10, 2022): e1010547. http://dx.doi.org/10.1371/journal.pcbi.1010547.
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A central function of continuous attractor networks is encoding coordinates and accurately updating their values through path integration. To do so, these networks produce localized bumps of activity that move coherently in response to velocity inputs. In the brain, continuous attractors are believed to underlie grid cells and head direction cells, which maintain periodic representations of position and orientation, respectively. These representations can be achieved with any number of activity bumps, and the consequences of having more or fewer bumps are unclear. We address this knowledge gap by constructing 1D ring attractor networks with different bump numbers and characterizing their responses to three types of noise: fluctuating inputs, spiking noise, and deviations in connectivity away from ideal attractor configurations. Across all three types, networks with more bumps experience less noise-driven deviations in bump motion. This translates to more robust encodings of linear coordinates, like position, assuming that each neuron represents a fixed length no matter the bump number. Alternatively, we consider encoding a circular coordinate, like orientation, such that the network distance between adjacent bumps always maps onto 360 degrees. Under this mapping, bump number does not significantly affect the amount of error in the coordinate readout. Our simulation results are intuitively explained and quantitatively matched by a unified theory for path integration and noise in multi-bump networks. Thus, to suppress the effects of biologically relevant noise, continuous attractor networks can employ more bumps when encoding linear coordinates; this advantage disappears when encoding circular coordinates. Our findings provide motivation for multiple bumps in the mammalian grid network.
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Burr, D., G. M. Cicchini, and G. Anobile. "Mapping number to space engages adaptive encoding mechanisms." Journal of Vision 14, no. 10 (August 22, 2014): 1423. http://dx.doi.org/10.1167/14.10.1423.
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Bettecken, Thomas, Brahim Aissani, Clemens R. Müller, and Giorgio Bernardi. "Compositional mapping of the human dystrophin-encoding gene." Gene 122, no. 2 (December 1992): 329–35. http://dx.doi.org/10.1016/0378-1119(92)90222-b.
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Kwon, O. J., M. C. Adamson, H. Chin, and C. A. Kozak. "Genetic mapping of five mouse genes encoding synaptotagmins." Mammalian Genome 6, no. 12 (December 1995): 880–81. http://dx.doi.org/10.1007/bf00292439.
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Drieb-Schön, Maike, Kilian Ender, Younes Javanmard, and Wolfgang Lechner. "Parity Quantum Optimization: Encoding Constraints." Quantum 7 (March 17, 2023): 951. http://dx.doi.org/10.22331/q-2023-03-17-951.
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Constraints make hard optimization problems even harder to solve on quantum devices because they are implemented with large energy penalties and additional qubit overhead. The parity mapping, which has been introduced as an alternative to the spin encoding, translates the problem to a representation using only parity variables that encodes products of spin variables. In combining exchange interaction and single spin flip terms in the parity representation, constraints on sums and products of arbitrary k-body terms can be implemented without additional overhead in two-dimensional quantum systems.
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Eckhoff, Hanne Martine, Olga A. Thomason, and Peter de Swart. "Mapping out the Source domain." Studies in Language 37, no. 2 (June 7, 2013): 302–55. http://dx.doi.org/10.1075/sl.37.2.03eck.
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This paper takes a strictly empirical approach to the encoding of spatial notions in the four ancient Indo-European languages Ancient Greek, Latin, Gothic and Old Church Slavonic. By generating semantic maps on the basis of parallel corpus data, without any semantic pre-analysis, we use methods well tested in typology to study the basic divisions in the spatial domain in the four closely-related languages, and to determine the finer subdivisions within the Source domain. We find that the four languages are similar, but clearly independent of each other, each carving up the spatial domain in different ways. We also find substantial encoding overlaps between the Source and Location domains.
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Abu Hilal, Tariq, Hasan Abu Hilal, and Ala Abu Hilal. "Multistage Arabic and Turkish Text Compression via Characters Encoding and 7-Zip." Journal of Ubiquitous Systems and Pervasive Networks 15, no. 01 (March 1, 2021): 11–15. http://dx.doi.org/10.5383/juspn.15.01.002.
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Turkish lossless text compression was proposed by converting the character’s from UTF-8 to ANSI system for space-preserving. Likewise, we present a decoding method that transforms the encoded ANSI string back to its original format. Unlike the one-byte ANSI characters, some of the Turkish alphabets are being stored in 2 bytes size. All that space comes at a price. The developed sequential encoding technique will reduce the size of the text file up to 9%. Moreover, the Turkish encoded text will retain its original form after decoding. According to our proposal, it is considered as a lossless text compression, where it’s a common concern today. Thus, many parties have become interested in Unicode compression. Basically, our algorithm is mapping Unicode Turkish characters into ANSI, by using the available 8-bit legacy. For Arabic Text Compression, a sequential encoding technique was suggested that efficiently converts Arabic characters string from UTF-8 to ANSI characters coding. The encoding algorithm presented in this paper significantly reduces the file size. The decoding method transforms the encoded ANSI string back to its original format. Unlike the one-byte ANSI characters, Arabic alphabets are currently being stored in 2 bytes size which leads to inefficient space utilization. The newly developed sequential encoding technique reduces the space required for storage up to fifty percent. In addition, the proposed technique will retain the Arabic encoded text to its original form after decoding, which is leading to a lossless text compression. Thus, addressing the common concern of the currently available Arabic characters compression techniques. In this research, a multistage compression process was implemented on Turkish and Arabic languages, by using the new encoding technique, in addition to the 7-Zip application, which has shown a significant file size reduction.
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Atir-Sharon, Tali, Asaf Gilboa, Hananel Hazan, Ester Koilis, and Larry M. Manevitz. "Decoding the Formation of New Semantics: MVPA Investigation of Rapid Neocortical Plasticity during Associative Encoding through Fast Mapping." Neural Plasticity 2015 (2015): 1–17. http://dx.doi.org/10.1155/2015/804385.
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Neocortical structures typically only support slow acquisition of declarative memory; however, learning through fast mapping may facilitate rapid learning-induced cortical plasticity and hippocampal-independent integration of novel associations into existing semantic networks. During fast mapping the meaning of new words and concepts is inferred, and durable novel associations are incidentally formed, a process thought to support early childhood’s exuberant learning. The anterior temporal lobe, a cortical semantic memory hub, may critically support such learning. We investigated encoding of semantic associations through fast mapping using fMRI and multivoxel pattern analysis. Subsequent memory performance following fast mapping was more efficiently predicted using anterior temporal lobe than hippocampal voxels, while standard explicit encoding was best predicted by hippocampal activity. Searchlight algorithms revealed additional activity patterns that predicted successful fast mapping semantic learning located in lateral occipitotemporal and parietotemporal neocortex and ventrolateral prefrontal cortex. By contrast, successful explicit encoding could be classified by activity in medial and dorsolateral prefrontal and parahippocampal cortices. We propose that fast mapping promotes incidental rapid integration of new associations into existing neocortical semantic networks by activating related, nonoverlapping conceptual knowledge. In healthy adults, this is better captured by unique anterior and lateral temporal lobe activity patterns, while hippocampal involvement is less predictive of this kind of learning.
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Besle, Julien, Rosa-Maria Sánchez-Panchuelo, Richard Bowtell, Susan Francis, and Denis Schluppeck. "Single-subject fMRI mapping at 7 T of the representation of fingertips in S1: a comparison of event-related and phase-encoding designs." Journal of Neurophysiology 109, no. 9 (May 1, 2013): 2293–305. http://dx.doi.org/10.1152/jn.00499.2012.
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A desirable goal of functional MRI (fMRI), both clinically and for basic research, is to produce detailed maps of cortical function in individual subjects. Single-subject mapping of the somatotopic hand representation in the human primary somatosensory cortex (S1) has been performed using both phase-encoding and block/event-related designs. Here, we review the theoretical strengths and limits of each method and empirically compare high-resolution (1.5 mm isotropic) somatotopic maps obtained using fMRI at ultrahigh magnetic field (7 T) with phase-encoding and event-related designs in six subjects in response to vibrotactile stimulation of the five fingertips. Results show that the phase-encoding design is more efficient than the event-related design for mapping fingertip-specific responses and in particular allows us to describe a new additional somatotopic representation of fingertips on the precentral gyrus. However, with sufficient data, both designs yield very similar fingertip-specific maps in S1, which confirms that the assumption of local representational continuity underlying phase-encoding designs is largely valid at the level of the fingertips in S1. In addition, it is shown that the event-related design allows the mapping of overlapping cortical representations that are difficult to estimate using the phase-encoding design. The event-related data show a complex pattern of overlapping cortical representations for different fingertips within S1 and demonstrate that regions of S1 responding to several adjacent fingertips can incorrectly be identified as responding preferentially to one fingertip in the phase-encoding data.
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Bone, Donald J. "Orthonormal Fractal Image Encoding Using Overlapping Blocks." Fractals 05, supp01 (April 1997): 187–99. http://dx.doi.org/10.1142/s0218348x97000759.
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This paper presents a novel approach to partitioned fractal image encoding. In this we seek to address a number of problems with earlier fractal encodings. These are: the artefacts associated with the block based approaches at high compression ratios; accuracy limitations imposed by the constraint that only one domain block is used to construct each range block; convergence problems which have required that constraints be imposed on the scaling coefficients to ensure that the mapping functions are contractive. These problems are addressed with a technique based on an orthonormal basis expansion using overlapping blocks, where the basis is partly fixed and partly derived from the image in such a way as to take advantage of local interscale self similarity. A fractal image codec based on this technique, which we call the Lapped Orthogonal Fractal Transform (LOFT), is described and tested, and the results are compared to those of other codecs.
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Nichele, Stefano, Andreas Giskeødegård, and Gunnar Tufte. "Evolutionary Growth of Genome Representations on Artificial Cellular Organisms with Indirect Encodings." Artificial Life 22, no. 1 (February 2016): 76–111. http://dx.doi.org/10.1162/artl_a_00191.
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Evolutionary design targets systems of continuously increasing complexity. Thus, indirect developmental mappings are often a necessity. Varying the amount of genotype information changes the cardinality of the mapping, which in turn affects the developmental process. An open question is how to find the genotype size and representation in which a developmental solution would fit. A restricted pool of genes may not be large enough to encode a solution or may need complex heuristics to find a realistic size. On the other hand, using the whole set of possible regulatory combinations may be intractable. In nature, the genomes of biological organisms are not fixed in size; they slowly evolve and acquire new genes by random gene duplications. Such incremental growth of genome information can be beneficial also in the artificial domain. For an evolutionary and developmental (evo-devo) system based on cellular automata, we investigate an incremental evolutionary growth of genomes without any a priori knowledge on the necessary genotype size. Evolution starts with simple solutions in a low-dimensional space and incrementally increases the genotype complexity by means of gene duplication, allowing the evolution of scalable genomes that are able to adapt genetic information content while compactness and efficiency are retained. The results are consistent when the target phenotypic complexity, the geometry size, and the number of cell states are scaled up.
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Fonseca i Casas, Pau, Daniel Lijia Hu, Antoni Guasch i Petit, and Jaume Figueras i Jové. "Simplifying the Verification of Simulation Models through Petri Net to FlexSim Mapping." Applied Sciences 10, no. 4 (February 19, 2020): 1395. http://dx.doi.org/10.3390/app10041395.
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Simplifying the encoding of a simulation conceptual model representation reduces the number of errors that will be detected in the verification phase. In this paper, we present a mapping between Petri nets, a well-known formalism, and FlexSim, a well-known simulation tool. The proposal is illustrated through an example of how a model specified in a Petri net can be encoded easily, reducing the time needed to understand and verify the model. In the proposed methodology, the mapping must be defined at the initial stage of the encoding, starting from (in this case) a Petri net conceptual model, and ending at the encoding tool (FlexSim in this case). The main advantages of the proposed methodology are discussed.
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Béguin, Pierre, Murielle Rocancourt, Marie-Christine Chebrou, and Jean-Paul Aubert. "Mapping of mRNA encoding endoglucanase A from Clostridium thermocellum." Molecular and General Genetics MGG 202, no. 2 (February 1986): 251–54. http://dx.doi.org/10.1007/bf00331645.
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Jie-Hong Jiang, Jing-Yang Jou, and Juinn-Dar Huang. "Unified functional decomposition via encoding for FPGA technology mapping." IEEE Transactions on Very Large Scale Integration (VLSI) Systems 9, no. 2 (April 2001): 251–60. http://dx.doi.org/10.1109/92.924031.
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Chin, Hemin, Myung Soo Lyu, Oh Joo Kwon, and Christine A. Kozak. "Genetic mapping of the gene encoding cysteine string protein." Mammalian Genome 8, no. 6 (June 1997): 456–57. http://dx.doi.org/10.1007/s003359900640.
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Gebser, Martin, Tomi Janhunen, and Jussi Rintanen. "Declarative encodings of acyclicity properties." Journal of Logic and Computation 30, no. 4 (September 8, 2015): 923–52. http://dx.doi.org/10.1093/logcom/exv063.
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Abstract Many knowledge representation tasks involve trees or similar structures as abstract datatypes. However, devising compact and efficient declarative representations of such structural properties is non-obvious and can be challenging indeed. In this article, we take a number of acyclicity properties into consideration and investigate various logic-based approaches to encode them. We use answer set programming as the primary representation language but also consider mappings to related formalisms, such as propositional logic, difference logic and linear programming. We study the compactness of encodings and the resulting computational performance on benchmarks involving acyclic or tree structures.