scholarly journals Intrinsic complexity of learning geometrical concepts from positive data

2003 ◽  
Vol 67 (3) ◽  
pp. 546-607 ◽  
Author(s):  
Sanjay Jain ◽  
Efim Kinber
2021 ◽  
Vol 11 (4) ◽  
pp. 519
Author(s):  
Tomas Poblete ◽  
Daniel Casanova ◽  
Miguel Soto ◽  
Alvaro Campero ◽  
Jorge Mura

The study of cerebrovascular anatomy can be difficult and may take time due to its intrinsic complexity. However, it can also be difficult for the following reasons: the excessive description of neuroanatomy making articles hard to read, the unclear clinical application of what is written, the use of simplified or intricate schematic drawings that are not always appropriate for effective teaching, the poor quality of neuroanatomy dissections and the use of unusual views of figures that are not strictly related to the most frequent neuroimages to be interpreted in daily practice. Because of this, we designed an article that incorporates original and accurate anatomical dissections in an attempt to improve its comprehensibility. Five formalin-fixed adult cadaveric heads, whose vessels were injected with a colored silicone mixture (red for arteries and blue for veins), were dissected and examined under a microscope with magnifications from 3× to 40×. Special emphasis has been placed on correlating topographic anatomy with routine neuroimaging studies from computed tomographic angiography (CTA) and digital subtraction angiography (DSA). The essential surgical anatomy in a neurosurgeon’s daily practice is also described. The cadaveric dissections included in this study contribute to the understanding of the cerebrovascular anatomy necessary for the neurosurgeon’s daily practice.


2021 ◽  
Vol 13 (11) ◽  
pp. 6303
Author(s):  
Andrea M. Bassi ◽  
Valeria Costantini ◽  
Elena Paglialunga

The European Green Deal (EGD) is the most ambitious decarbonisation strategy currently envisaged, with a complex mix of different instruments aiming at improving the sustainability of the development patterns of the European Union in the next 30 years. The intrinsic complexity brings key open questions on the cost and effectiveness of the strategy. In this paper we propose a novel methodological approach to soft-linking two modelling tools, a systems thinking (ST) and a computable general equilibrium (CGE) model, in order to provide a broader ex-ante policy evaluation process. We use ST to highlight the main economic feedback loops the EGD strategy might trigger. We then quantify these loops with a scenario analysis developed in a dynamic CGE framework. Our main finding is that such a soft-linking approach allows discovery of multiple channels and spillover effects across policy instruments that might help improve the policy mix design. Specifically, positive spillovers arise from the adoption of a revenue recycling mechanism that ensures strong support for the development and diffusion of clean energy technologies. Such spillover effects benefit not only the European Union (EU) market but also non-EU countries via trade-based technology transfer, with a net positive effect in terms of global emissions reduction.


Nutrients ◽  
2019 ◽  
Vol 11 (5) ◽  
pp. 962 ◽  
Author(s):  
Bolla ◽  
Caretto ◽  
Laurenzi ◽  
Scavini ◽  
Piemonti

Low-carb and ketogenic diets are popular among clinicians and patients, but the appropriateness of reducing carbohydrates intake in obese patients and in patients with diabetes is still debated. Studies in the literature are indeed controversial, possibly because these diets are generally poorly defined; this, together with the intrinsic complexity of dietary interventions, makes it difficult to compare results from different studies. Despite the evidence that reducing carbohydrates intake lowers body weight and, in patients with type 2 diabetes, improves glucose control, few data are available about sustainability, safety and efficacy in the long-term. In this review we explored the possible role of low-carb and ketogenic diets in the pathogenesis and management of type 2 diabetes and obesity. Furthermore, we also reviewed evidence of carbohydrates restriction in both pathogenesis of type 1 diabetes, through gut microbiota modification, and treatment of type 1 diabetes, addressing the legitimate concerns about the use of such diets in patients who are ketosis-prone and often have not completed their growth.


2015 ◽  
Vol 32 (6) ◽  
pp. 835-842 ◽  
Author(s):  
Filippo Utro ◽  
Valeria Di Benedetto ◽  
Davide F.V. Corona ◽  
Raffaele Giancarlo

Abstract Motivation: Thanks to research spanning nearly 30 years, two major models have emerged that account for nucleosome organization in chromatin: statistical and sequence specific. The first is based on elegant, easy to compute, closed-form mathematical formulas that make no assumptions of the physical and chemical properties of the underlying DNA sequence. Moreover, they need no training on the data for their computation. The latter is based on some sequence regularities but, as opposed to the statistical model, it lacks the same type of closed-form formulas that, in this case, should be based on the DNA sequence only. Results: We contribute to close this important methodological gap between the two models by providing three very simple formulas for the sequence specific one. They are all based on well-known formulas in Computer Science and Bioinformatics, and they give different quantifications of how complex a sequence is. In view of how remarkably well they perform, it is very surprising that measures of sequence complexity have not even been considered as candidates to close the mentioned gap. We provide experimental evidence that the intrinsic level of combinatorial organization and information-theoretic content of subsequences within a genome are strongly correlated to the level of DNA encoded nucleosome organization discovered by Kaplan et al. Our results establish an important connection between the intrinsic complexity of subsequences in a genome and the intrinsic, i.e. DNA encoded, nucleosome organization of eukaryotic genomes. It is a first step towards a mathematical characterization of this latter ‘encoding’. Supplementary information: Supplementary data are available at Bioinformatics online. Contact: [email protected].


2015 ◽  
Vol 79 (1-3) ◽  
pp. 181-203
Author(s):  
Seishi Ouchi ◽  
Tomohiko Okayama ◽  
Keisuke Otaki ◽  
Ryo Yoshinaka ◽  
Akihiro Yamamoto

2000 ◽  
Vol 11 (03) ◽  
pp. 515-524
Author(s):  
TAKESI OKADOME

The paper deals with learning in the limit from positive data. After an introduction and overview of earlier results, we strengthen a result of Sato and Umayahara (1991) by establishing a necessary and sufficient condition for the satisfaction of Angluin's (1980) finite tell-tale condition. Our other two results show that two notions introduced here, the finite net property and the weak finite net property, lead to sufficient conditions for learning in the limit from positive data. Examples not solvable by earlier methods are also given.


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