Automorphisms of prime order of smooth cubic n-folds

In this paper we give an effective criterion as to when a prime number p is the order of an automorphism of a smooth cubic hypersurface of P^{n+1}, for a fixed n > 1. We also provide a computational method to classify all such hypersurfaces that admit an automorphism of prime order p. In particular, we show that p<2^{n+1} and that any such hypersurface admitting an automorphism of order p>2^n is isomorphic to the Klein n-fold. We apply our method to compute exhaustive lists of automorphism of prime order of smooth cubic threefolds and fourfolds. Finally, we provide an application to the moduli space of principally polarized abelian varieties.Comment: 10 page

A Comparison of Machine-Learning Methods to Select Socioeconomic Indicators in Cultural Landscapes

Cultural landscapes are regarded to be complex socioecological systems that originated as a result of the interaction between humanity and nature across time. Cultural landscapes present complex-system properties, including nonlinear dynamics among their components. There is a close relationship between socioeconomy and landscape in cultural landscapes, so that changes in the socioeconomic dynamic have an effect on the structure and functionality of the landscape. Several numerical analyses have been carried out to study this relationship, with linear regression models being widely used. However, cultural landscapes comprise a considerable amount of elements and processes, whose interactions might not be properly captured by a linear model. In recent years, machine-learning techniques have increasingly been applied to the field of ecology to solve regression tasks. These techniques provide sound methods and algorithms for dealing with complex systems under uncertainty. The term ‘machine learning’ includes a wide variety of methods to learn models from data. In this paper, we study the relationship between socioeconomy and cultural landscape (in Andalusia, Spain) at two different spatial scales aiming at comparing different regression models from a predictive-accuracy point of view, including model trees and neural or Bayesian networks

The Role of Cultural Landscapes in the Delivery of Provisioning Ecosystem Services in Protected Areas

The aim of this paper is to assess and highlight the significance of cultural landscapes in protected areas, considering both biodiversity and the delivery of provisioning ecosystem services. In order to do that, we analyzed 26 protected areas in Andalusia (Spain), all of them Natural or National Parks, regarding some of their ecosystem services (agriculture, livestock grazing, microclimate regulation, environmental education and tourism) and diversity of the four terrestrial vertebrate classes: amphibians, reptiles, mammals, and birds. A cluster analysis was also run in order to group the 26 protected areas according to their dominant landscape. The results show that protected areas dominated by dehesa (a heterogeneous system containing different states of ecological maturity), or having strong presence of olive groves, present a larger area of delivery of provisioning ecosystem services, on average. These cultural landscapes play an essential role not only for biodiversity conservation but also as providers of provisioning ecosystem services

Transcription-mediated replication hindrance: a major driver of genome instability

Genome replication involves dealing with obstacles that can result from DNA damage but also from chromatin alterations, topological stress, tightly bound proteins or non-B DNA structures such as R loops. Experimental evidence reveals that an engaged transcription machinery at the DNA can either enhance such obstacles or be an obstacle itself. Thus, transcription can become a potentially hazardous process promoting localized replication fork hindrance and stress, which would ultimately cause genome instability, a hallmark of cancer cells. Understanding the causes behind transcription–replication conflicts as well as how the cell resolves them to sustain genome integrity is the aim of this review

Analyzing Uncertainty in Complex Socio-Ecological Networks

Socio-ecological systems are recognized as complex adaptive systems whose multiple interactions might change as a response to external or internal changes. Due to its complexity, the behavior of the system is often uncertain. Bayesian networks provide a sound approach for handling complex domains endowed with uncertainty. The aim of this paper is to analyze the impact of the Bayesian network structure on the uncertainty of the model, expressed as the Shannon entropy. In particular, three strategies for model structure have been followed: naive Bayes (NB), tree augmented network (TAN) and network with unrestricted structure (GSS). Using these network structures, two experiments are carried out: (1) the impact of the Bayesian network structure on the entropy of the model is assessed and (2) the entropy of the posterior distribution of the class variable obtained from the different structures is compared. The results show that GSS constantly outperforms both NB and TAN when it comes to evaluating the uncertainty of the entire model. On the other hand, NB and TAN yielded lower entropy values of the posterior distribution of the class variable, which makes them preferable when the goal is to carry out predictions

Rpd3L and Hda1 histone deacetylases facilitate repair of broken forks by promoting sister chromatid cohesion

Genome stability involves accurate replication and DNA repair. Broken replication forks, such as those encountering a nick, lead to double strand breaks (DSBs), which are preferentially repaired by sister-chromatid recombination (SCR). To decipher the role of chromatin in eukaryotic DSB repair, here we analyze a collection of yeast chromatin-modifying mutants using a previously developed system for the molecular analysis of repair of replication-born DSBs by SCR based on a mini-HO site. We confirm the candidates through FLP-based systems based on a mutated version of the FLP flipase that causes nicks on either the leading or lagging DNA strands. We demonstrate that Rpd3L and Hda1 histone deacetylase (HDAC) complexes contribute to the repair of replication-born DSBs by facilitating cohesin loading, with no effect on other types of homology-dependent repair, thus preventing genome instability. We conclude that histone deacetylation favors general sister chromatid cohesion as a necessary step in SCR

Exploring RCNN for the automated analysis of paramagnetic rim lesions in Multiple Sclerosis MRI

In multiple sclerosis, lesions with a peripheral paramagnetic rim is a negative prognostic imaging biomarker and represents a potential outcome measure in MRI-based clinical trials. Nowadays, the presence or absence of paramagnetic rims is determined through visual inspection by medical experts, which is tedious, time consuming and prone to observer variability. So far, few solutions to the automated classification of rims problem have been proposed. These studies present limitations that represent an obstacle to full automation of the rim analysis process and its large-scale application. Our goal is to implement and assess a fully automated algorithm capable of identifying rim lesions in MRI. In this work, we explore a Region-proposal CNN deep learning approach to solve the fully automated rim lesions classification problem that perform instance segmentation by object detection and have shown promising results in recent challenges, particularly in medical imaging. After different approaches focus on implifying the task, Mask RCNN with MobileNet v2 as backbone using attention gaussian filtering to the input images showed better performance than the rest with rates of 0.42 TPR and 0.61 FPR for the test set. However, the achieved results reveal the weaknesses of our approach and the difficulty of our classification problem

The Impact of Strategies in Supply Chain Management for Better Performance in Manufacturing SMEs in Aguascalientes

This research aims to analyze the impact of the implementation of strategies in the the Supply Chain Management (SCM), Manufacturing for SMEs in Aguascalientes may have a higher yield. The analysis was performed through the design of an assessment tool aimed at managers through an empirical study in the period from August to December 2013. The methodology has been quantitative approach, as well as correlational and descriptive the sample is random. The expected results are intended to influence the decisions taken by the managers in their organizations to the SCM is still complex, it is more efficient through the implementation of strategies for increased output in manufacturing SMEs in Aguascalientes. In this sense, the expected results intended sizing how important the integration of strategies is in the practice of the SCM, and in turn, the impact of this influence on the Performance of Manufacturing SMEs. In this study, structural equation modeling technique was applied to support software EQS 6.

Análisis de la relación entre las prácticas de evaluación de estudiantes en la Facultad de Ingeniería de la U.C de C. y la propuesta institucional de evaluación basada en competencias

Trabajo de investigaciónAnálisis de una propuesta institucional de evaluación de los procesos educativos de los estudiantes contra la practica evaluativa, para el análisis se retomaron los referentes de evaluación, de competencias que enmarcan el acto educativo de los Instituciones de Educación Superior (IES) y como estas convergen en dar una visión de la evaluación como herramienta fundamental del proceso formativo.MaestríaMagister en Psicologí