A complexity analysis of functional interpretations

The fact that classical mathematical proofs of simply existential statements\ncan be read as programs was established by Goedel and Kreisel half a century\nago. But the possibility of extracting useful computational content from\nclassical proofs was taken seriously only from the 1990s on when it was\ndiscovered that proof interpretations based on Goedel's and Kreisel's ideas can\nprovide new nontrivial algorithms and numerical results, and the Curry-Howard\ncorrespondence can be extended to classical logic via programming concepts such\nas continuations and control operators.\n The workshop series "Classical Logic and Computation" aims to support a\nfruitful exchange of ideas between the various lines of research on\ncomputational aspects of classical logic. This volume contains the abstracts of\nthe invited lectures and the accepted contributed papers of the third CL&C\nworkshop which was held jointly with the workshop "Program Extraction and\nConstructive Mathematics" at the University of Brno in August 21-22, 2010, as a\nsatellite of CSL and MFCS. The workshops were held in honour of Helmut\nSchwichtenberg who became "professor emeritus" in September 2010.\n The topics of the papers include the foundations, optimizations and\napplications of proof interpretations such as Hilbert's epsilon substitution\nmethod, Goedel's functional interpretation, learning based realizability and\nnegative translations as well as special calculi and theories capturing\ncomputational and complexity-theoretic aspects of classical logic such as the\nlambda-mu-calculus, applicative theories, sequent-calculi, resolution and\ncut-elimination\n

The rapid expansion of available three-dimensional protein structures-derived from both experimental techniques and bioinformatic predictions-offers unprecedented opportunities for drug discovery, particularly for targets that have historically been difficult to characterize. However, the effective analysis of these increasingly complex and voluminous structural datasets remains a major challenge. Efficient representations of protein conformations are essential to facilitate large-scale comparison, structural classification, and functional interpretation in therapeutic contexts. The concept of structural alphabets, introduced by Pr S. Hazout in 1999, provides a robust and scalable framework to represent local protein backbone conformations using a limited set of recurring structural motifs. This representation enables a one-dimensional encoding of three-dimensional protein structures that retains essential geometric features beyond secondary structure, while allowing systematic and interpretable analyses. In this review, we focus on HMM-SA, a structural alphabet constructed using a hidden Markov model. HMM-SA defines 27 structural motifs, including 18 regions specifically dedicated to loops, and captures the statistical dependencies between them. We present a detailed overview of the HMM-SA framework, and of the computational tools derived from this structural alphabet, developed to explore protein function, conformational variability, and the structural determinants of molecular recognition. The utility of HMM-SA is illustrated through a case study on HIV-2 protease (PR2), a critical enzyme in antiretroviral drug development. By analyzing PR2 structural asymmetry, ligand-induced conformational changes, and mutation-driven alterations, we highlight the ability of HMM-SA-based methods to identify key structural features involved in ligand specificity and resistance mechanisms, thereby advancing therapeutic target analysis.

We give a Natural Deduction formulation of an adaptation of Gödel’s functional (Dialectica) interpretation to the extraction of (more) efficient programs from (classical) proofs. We adapt Jørgensen’s formulation of pure Dialectica translation by eliminating his “Contraction Lemma” and allowing free variables in the extracted terms (which is more suitable in a Natural Deduction setting). We also adapt Berger’s uniform existential and universal quantifiers to the Dialectica-extraction context. The use of such quantifiers without computational meaning permits the identification and isolation of contraction formulas which would otherwise be redundantly included in the pure-Dialectica extracted terms. In the end we sketch the possible combination of our refinement of Gödel’s Dialectica interpretation with its adaptation to the extraction of bounds due to Kohlenbach into a light monotone functional interpretation.KeywordsProgram extraction from (classical) proofsComplexity of extracted programsBerger’s uniform quantifiersGödel’s Functional interpretationProof-Carrying CodeProof Mining

ABSTRACTIn the following article, we share our findings from the comparative analyses of 54 lifelong learning policy measures implemented in nine European countries, with a particular focus on their orientations, objectives, and solutions devised. Informed by the theoretical framework of Interpretive Policy Analysis (IPA), we have further reasoned on the impacts and unintended effects on young adults’ life course transitions, especially those in vulnerable positions, as well as on the hidden ambivalences and incompatibilities in the objectives and orientations of lifelong learning policies. The article provides, first, a brief discussion of the conceptual and methodological choices made. Second, it gives an overview of the design and data basis of our research. In the third section, we present and discuss the central findings from our interpretive analyses, and we finally conclude with a discussion on current trends in lifelong learning policymaking and on their impact on young adults’ transitions.

Metaphor use is characterised by conceptual variation that can be explained with reference to culture-specific discourse traditions. Cognitively oriented metaphor analyses that are interested in cultural relativity have so far concentrated mainly on the production side of metaphors and their misunderstanding by ESL learners. This study, by contrast, focuses on variation in metaphor interpretation across groups of ESL/EFL users from 31 cultural and linguistic backgrounds. Its data consist of a questionnaire survey, administered in 10 countries, which gave students the task of applying the metaphor of the “body politic” to one’s home nation. The results show systematic variation between four interpretation models for this metaphor, i.e. NATION AS GEOBODY, NATION AS FUNCTIONAL WHOLE, NATION AS PART OF SELF and NATION AS PART OF INTERNATIONAL/GLOBAL STRUCTURE, as well as some evidence of elaborate polemical and/or political elaboration. The two main versions, i.e. NATION AS GEOBODY and NATION AS FUNCTIONAL WHOLE, were represented across all cohorts but exhibited opposite frequency patterns across Chinese v. Western cohorts, with the former favouring GEOBODY-based, the latter functional interpretations. This finding and the evidence of elaborate metaphor interpretations lead to culture-specific motivations of variation in metaphor interpretation (as well as in metaphor production), specifically with regard to the frequency and distribution patterns of source concepts. Metaphor interpretation analysis can thus contribute to a cognitive metaphor analysis in general and especially to “cultural linguistics” approach to metaphor.

Abstract. Urban information extraction from satellite based remote sensing data could provide the basic scientific decision-making data for the construction and management of future cities. In particular, long-term satellite based remote sensing such as Landsat observations provides a rich source of data for urban area mapping. Urban area mapping based on the single-temporal Landsat observations is vulnerable to data quality (such as cloud coverage and stripe), and it is difficult to extract urban areas accurately. The composite of dense time series Landsat observations can significantly reduce the effect of data quality on urban area mapping. Multidimensional array is currently effective theory for geographic big data analysis and management, providing a theoretical basis for the composite of dense time series Landsat observations. Google Earth Engine (GEE) not only provides rich satellite based remote sensing data for the composite of dense time series data, but also has powerful massive data analysis capabilities. In the study, we chose Random Forest (RF) algorithm for the urban area extraction owing to its stable performance, high classification accuracy and feature importance evaluation. In this work, the study area is located in the central part of the city of Beijing, China. Our main data source is all Landsat8 OLI images in Beijing (path/row: 123/32) in 2017.Based on the multidimensional array for geographic big data theory and the GEE cloud computing platform, four commonly used reducer methods are selected to composite the annual dense time series Landsat 8 OLI data. After collecting the training samples, RF algorithm was selected for supervised classification, feature importance evaluation and accuracy verification for urban area mapping. The results showed that 1), compared with the single temporal image of Landsat 8 OLI, the quality of annual composite image was improved obviously, especially for urban extraction in cloudy areas; 2) for the evaluation results of feature importance based on RF algorithm, Coastal, Blue, NIR, SWIR1 and SWIR2 bands were the more important characteristic bands, while the Green and Red bands were comparatively less important; 3) the annual composite images obtained by the ee.Reducer.min, ee.Reducer.max, ee.Reducer.mean and ee.Reducer.median methods were classified and accuracy verification was carried out using the verification points. The overall accuracy of the urban area mapping reached 0.805, 0.820, 0.868 and 0.929, respectively. In summary, the ee.Reducer.median method is a suitable method for annual dense time series Landsat image composite, which could improve the data quality, and ensure the difference of features and the higher accuracy of urban area mapping.

Knuckle-walking in Sivapithecus? The combined effects of homology and homoplasy with possible implications for pongine dispersals

Dissecting the global variation of gene expression for the functional interpretation of transcriptome data

In order to generate cartographic data bases, it is necessary to digitize a large number of existing base maps. One way of replacing the error-prone and very time-consuming manual digitization by an automatic method is scanning the map and extracting the linework from the resulting binary matrix. A sufficiently fast and economic scan-to-line-conversion algorithm has to be developed for the line extraction.The algorithm presented operates with a skeletonization technique which is further developed from known line thinning methods, so that the scan lines are now skeletonized in a single pass and that only a small number of scan lines has to be held in core storage. The result of this process is equivalent to a multi-pass skeletonization which utilizes a quasi-parallel line thinning in four partitions of the binary matrix for each pass.The data produced by the extraction algorithm following the skeletonization have two important advantages over data produced by manual digitization: First, the nodes corresponding to the line end points are exactly determined and, second, the correction phase is shortened since the automatic process is less error-prone.Time and storage requirements of the implemented algorithm applied to some typical scan data show that the conversion for even a complex line structure can be carried out within the time of scanning and the economic use of core storage makes it possible to implement the algorithm on a minicomputer with an on-line scanner.

This paper focuses on the design of an improved Discrete Fast Walsh Hadamard Transform (DFWHT) domain digital image watermarking algorithm and its low complexity as well as fast hardware architecture implementation on Xilinx based (version 14.7 Virtex-7 series) FPGA with target device xc7vx1140t-1flg1930, with maximum achieved frequency of 259.202 MHz. The architecture proposed here is to our best knowledge is the first architecture for the corresponding algorithm. Both encoding and extraction algorithm have been verified using MATLAB R2013a. Both gray scale and binary watermarks are used and only gray scale cover image of maximum size (256 x 256) is used. The algorithm and the architecture is applicable for both gray scale and binary watermarks.

Rationale: We previously found oropharyngeal enlargement and subglottal narrowing in asthma and chronic obstructive pulmonary disease (COPD) patients compared to healthy individuals. This study aimed to investigate the impact of oropharyngeal remodeling on the upper airway airflow dynamics in association with lung structure-function impairment in obstructive lung disease (OLD). Methods: Upper airway computed tomography (CT) scans, inspiratory (total lung capacity) and expiratory (functional residual capacity) lung CTs, and clinical data were collected from 185 participants (26 healthy, 56.6±5.1y; 73 COPD, 71.1±7.5y, and 86 asthma, 64.8±12.5y) enrolled in Jeonbuk National University Hospital, Jeonju, Korea. We conducted quantitative inspiratory-expiratory CT analysis and one-dimensional (1D) computational fluid dynamics (CFD) simulations of airflow in the lower airways, for all participants. Then, we selected ten representative subjects in each group based on key features of upper airways (healthy: 56±6.2y; COPD: 69.7±7.4y; asthma: 63.2±6.3y) and conducted three-dimensional (3D) CFD simulations of breathing (tidal volume: 6 ml/kg). Results: Patients with OLD showed 11 times greater CFD-derived lower airway resistance and 3.8% smaller transpulmonary pressure than healthy controls. 3D CFD simulations showed less pressure drop from the mouth to the level of the sixth cervical vertebra (C6) during inhalation in OLD (COPD: 37.3±41.9Pa; asthma: 32.01±18.4 Pa) than in healthy subjects (70.7±48.5) Pa. Upper (oropharyngeal) airway resistance was also smaller in OLD (COPD: 155.0±188.0 kPa·s/m³; asthma: 116.2±61.5 kPa·s/m³) than in healthy subjects (229.4±142.2 kPa·s/m³). This is attributable to oropharyngeal enlargement measured by greater oral space air fraction and larger supraglottal airway diameter at the level of the fourth cervical vertebra (C4). Less upper airway pressure drop to the level of C6 correlated with upper airway enlargement measured by normalized upper airway air volume (r=-0.60, p<0.001) and diameter at C4 (r=-0.56, p=0.001) as well as lung structure-function impairment such as functional small airways disease percent (fSAD%), less volumetric deformation (J), and less relative displacement (s[asterisk]) (r=-0.40, 0.47, 0.54; p=0.030, 0.009, 0.002) and worse spirometry outcomes such as post-BD FEV1% (r=0.54, p=0.002) and FEV1/FVC (r=0.54, p=0.002). Conclusion: CT-based CFD simulations showed patients with obstructive lung disease experienced elevated airway resistance in the lower airways but reduced pressure drop and airway resistance due to oropharyngeal enlargement during inhalation. Reduced aerodynamic effort may help compensate excessive respiratory effort required in the lower airways. Findings suggest that upper airway imaging and airflow analysis allows more complete interpretation of the entire respiratory function altered with airflow obstruction.

In this paper, we consider induced subgraphs of the Hamming graph $H(n,3)$. We show that if $U \subseteq \mathbb{Z}_3^n$ and $U$ induces a subgraph of $H(n,3)$ with maximum degree at most $1$ then 1. If $U$ is disjoint from a maximum size independent set of $H(n,3)$ then $|U| \leq 3^{n-1}+1$. Moreover, all such $U$ with size $3^{n-1}+1$ are isomorphic to each other. 2. For $n \geq 6$, there exists such a $U$ with size $|U| = 3^{n-1}+18$ and this is optimal for $n = 6$. 3. If $U \cap \{x, x+e_1, x+2e_1\} \ne ϕ$ for all $x \in \mathbb{Z}_3^n$ then $|U| \leq 3^{n-1} + 81$. 41 pages. This is the journal version of our paper

International audience

We propose a snapshot hyperspectral imaging system and methods for skin morphological feature analysis and real-time monitoring of skin activities. The analysis method includes a strategy using weighted subtractions between sub-channel images to extract absorption information due to specific chromophores within skin tissue, for example hemoglobin and melanin. Based on morphological analysis results, we carry out real-time monitoring of the skin features to verify the ability of this method to provide temporal responses of the skin tissue activities, which is experimentally shown to be useful in the measurement of heartrate, monitoring of the tissue recovery after a body exercise, and studying of the tissue response due to a vascular occlusion. Compared to conventional multispectral imaging system, the proposed system improves the device simplicity and is immune to motion artifacts. Coupled with the extraction algorithms, the hyperspectral imaging promises a robust skin assessment tool with abilities for qualitative visualization and potentially quantitative analysis of skin features, useful in the applications of cosmetics and clinical dermatology.

On the maximum size of stepwise irregular graphs