Higher education in industrial engineering in Peru: towards a new model based on skills

This article analyzes the progress of Industrial Engineering in Peru, the relationship to major trends in Europe and North America, and the projected outlook for the future. It is determined that the need for this engineering specialty includes a significant degree of resource management, and the formation of engineers through education requires not only the acquisition and strengthening of technical knowledge, but also the development of the competences that are required by both employers and the recipients of the benefits of engineering: society. Conclusions have been drawn based on state-of-the-art analyses from Europe and North America, and definitions of trends for engineering.

A neuronal model of a global workspace in effortful cognitive tasks

A minimal hypothesis is proposed concerning the brain processes underlying effortful tasks. It distinguishes two main computational spaces: a unique global workspace composed of distributed and heavily interconnected neurons with long-range axons, and a set of specialized and modular perceptual, motor, memory, evaluative, and attentional processors. Workspace neurons are mobilized in effortful tasks for which the specialized processors do not suffice. They selectively mobilize or suppress, through descending connections, the contribution of specific processor neurons. In the course of task performance, workspace neurons become spontaneously coactivated, forming discrete though variable spatio-temporal patterns subject to modulation by vigilance signals and to selection by reward signals. A computer simulation of the Stroop task shows workspace activation to increase during acquisition of a novel task, effortful execution, and after errors. We outline predictions for spatio-temporal activation patterns during brain imaging, particularly about the contribution of dorsolateral prefrontal cortex and anterior cingulate to the workspace.

The RESID Database of protein structure modifications and the NRL-3D Sequence–Structure Database

The RESID Database is a comprehensive collection of annotations and structures for protein post-translational modifications including N-terminal, C-terminal and peptide chain cross-link modifications. The RESID Database includes systematic and frequently observed alternate names, Chemical Abstracts Service registry numbers, atomic formulas and weights, enzyme activities, taxonomic range, keywords, literature citations with database cross-references, structural diagrams and molecular models. The NRL-3D Sequence–Structure Database is derived from the three-dimensional structure of proteins deposited with the Research Collaboratory for Structural Bioinformatics Protein Data Bank. The NRL-3D Database includes standardized and frequently observed alternate names, sources, keywords, literature citations, experimental conditions and searchable sequences from model coordinates. These databases are freely accessible through the National Cancer Institute–Frederick Advanced Biomedical Computing Center at these web sites: http://www.ncifcrf.gov/RESID, http://www.ncifcrf.gov/ NRL-3D; or at these National Biomedical Research Foundation Protein Information Resource web sites: http://pir.georgetown.edu/pirwww/dbinfo/resid.html, http://pir.georgetown.edu/pirwww/dbinfo/nrl3d.html

Comparison of the defensive elicitation activity of cerato-populin and cerato-platanin: a structural model

Plants can defend themselves from potential pathogenic microorganisms relying on a complex interplay of signaling pathways: activation of the MAPK cascade, transcription of defense related genes, production of reactive oxygen species, nitric oxide and synthesis of other defensive compounds such as phytoalexins. These events are triggered by the recognition of pathogen’s effectors (effector-triggered immunity) or PAMPs (PAMP-triggered immunity). The Cerato Platanin Family (CPF) members are Cys-rich proteins secreted and localized on fungal cell walls, involved in several aspects of fungal development and pathogen-host interactions. Although more than hundred genes of the CPF have been identified and analyzed, the structural and functional characterization of the expressed proteins has been restricted only to few members of the family. Interestingly, those proteins have been shown to bind chitin with diverse affinity and after foliar treatment they elicit defensive mechanisms in host and non-host plants. This property turns cerato platanins into interesting candidates, worth to be studied to develop new fungal elicitors with applications in sustainable agriculture. This study focus on cerato-platanin (CP), core member of the family and on the orthologous cerato-populin (Pop1). The latter shows an identity of 62% and an overall homology of 73% with respect to CP. Both proteins are able to induce MAPKs phosphorylation, production of reactive oxygen species and nitric oxide, overexpression of defense’s related genes, programmed cell death and synthesis of phytoalexins. CP, however, when compared to Pop1, induces a faster response and, in some cases, a stronger activity on plane leaves. Aim of the present research is to verify if the dissimilarities observed in the defense elicitation activity of these proteins can be associated to their structural and dynamic features. Taking advantage of the available CP NMR structure, Pop1’s 3D one was obtained by homology modeling. Experimental residual dipolar couplings and 1H, 15N, 13C resonance assignments were used to validate the model. Previous works on CPF members, addressed the highly conserved random coil regions (loops b1-b2 and b2-b3) as sufficient and necessary to induce necrosis in plants’ leaves: that region was investigated in both Pop1 and CP. In the two proteins the loops differ, in their primary sequence, for few mutations and an insertion with a consequent diversification of the proteins’ electrostatic surface. A set of 2D and 3D NMR experiments was performed to characterize both the spatial arrangement and the dynamic features of the loops. NOE data revealed a more extended network of interactions between the loops in Pop1 than in CP. In addition, in Pop1 we identified a salt bridge Lys25/Asp52 and a strong hydrophobic interaction between Phe26/Trp53. These structural features were expected not only to affect the loops’ spatial arrangement, but also to reduce the degree of their conformational freedom. Relaxation data and the order parameter S2 indeed highlighted reduced flexibility, in particular for loop b1-b2 of Pop1. In vitro NMR experiments, where Pop1 and CP were titrated with oligosaccharides, supported the hypothesis that the loops structural and dynamic differences may be responsible for the different chitin-binding properties of the two proteins: CP selectively binds tetramers of chitin in a shallow groove on one side of the barrel defined by loops b1-b2, b2-b3 and b4-b5, Pop1, instead, interacts in a non-specific fashion with oligosaccharides. Because the region involved in chitin-binding is also responsible for the defense elicitation activity, possibly being recognized by plant's receptors, it is reasonable to expect that those structural and dynamic modifications may also justify the different extent of defense elicitation. To test that hypothesis, the initial steps of a protocol aimed to the identify a receptor for CP, in silico, are presented.

Avaliação em 3D da cabeça da mandíbula em crianças portadoras de mordida cruzada posterior unilateral por meio de tomografia computadorizada de feixe cônico

Durante o desenvolvimento da oclusão, a instalação de maloclusões podem resultar em desarmonias dento faciais de natureza e severidade diversas, podendo provocar alterações no desenvolvimento crânio facial, dentre as estruturas envolvidas as Articulações Temporo Mandibulares (ATM), podem sofrer alguma influência, dessa forma a avaliação desta região, no aspecto morfológico e funcional, constituí tema de interesse, sempre que levados em conta os aspectos funcionais da oclusão. A relação entre a forma e a função, tanto das cabeças da mandíbula, bem como o contorno da fossa mandibular com as maloclusões ainda é controversa e não está compreendida por completo, porém a literatura sobre o assunto, demonstra correlação entre a instalação de maloclusões e modificações neste sistema, mesmo que algumas alterações não sejam de ordem estatística e em amostras de indivíduos em tenra idade, as mesmas podem comprometer o desenvolvimento adequado em indivíduos adultos ou mesmo adultos jovens. Tendo como propósito nesse estudo a avaliação das cabeças da mandíbula quanto ao volume e superficíe dos lados direito e esquerdo, cruzado e não cruzado, a amostra selecionada foi de 20 indivíduos com mordida cruzada posterior unilateral, com idades entre 06 e 09 anos de idade, utilizando imagens de tomografia computadorizada por feixe cônico, imagens obtidas por um equipamento modelo i- Cat, sendo utilizado na reformatação e manipulação das imagens o programa computacional - NemoCeph 3D® versão 11.5. Nas medições propostas para esse estudo, utilizou-se o teste t pareado de Student para amostras com distribuição normal. Na observação das tabelas e seus respectivos gráficos, podemos verificar que na comparação entre os lados direito e esquerdo, e cruzado e não cruzado das cabeças da mandíbula, com relação ao volume e superfície, existem diferenças numéricas entre elas, porém não pode ser observado diferenças estatísticas significantes, nessa amostra especifica com a metodologia empregada para esse estudo. Assim foi possível concluir que nas Mordidas Cruzadas Posteriores Unilaterais as cabeças da mandíbula tanto em seu volume como em sua superfície não apresentaram diferenças estatisticamente significantes na amostra estudada.

Condensados de Bose-Einstein em redes óticas: a transição superfluido-isolante de Mott em redes hexagonais e a classe de universalidade superfluido-vidro de Bose em 3D

Estudamos transições de fases quânticas em gases bosônicos ultrafrios aprisionados em redes óticas. A física desses sistemas é capturada por um modelo do tipo Bose-Hubbard que, no caso de um sistema sem desordem, em que os átomos têm interação de curto alcance e o tunelamento é apenas entre sítios primeiros vizinhos, prevê a transição de fases quântica superfluido-isolante de Mott (SF-MI) quando a profundidade do potencial da rede ótica é variado. Num primeiro estudo, verificamos como o diagrama de fases dessa transição muda quando passamos de uma rede quadrada para uma hexagonal. Num segundo, investigamos como a desordem modifica essa transição. No estudo com rede hexagonal, apresentamos o diagrama de fases da transição SF-MI e uma estimativa para o ponto crítico do primeiro lobo de Mott. Esses resultados foram obtidos usando o algoritmo de Monte Carlo quântico denominado Worm. Comparamos nossos resultados com os obtidos a partir de uma aproximação de campo médio e com os de um sistema com uma rede ótica quadrada. Ao introduzir desordem no sistema, uma nova fase emerge no diagrama de fases do estado fundamental intermediando a fase superfluida e a isolante de Mott. Essa nova fase é conhecida como vidro de Bose (BG) e a transição de fases quântica SF-BG que ocorre nesse sistema gerou muitas controvérsias desde seus primeiros estudos iniciados no fim dos anos 80. Apesar dos avanços em direção ao entendimento completo desta transição, a caracterização básica das suas propriedades críticas ainda é debatida. O que motivou nosso estudo, foi a publicação de resultados experimentais e numéricos em sistemas tridimensionais [Yu et al. Nature 489, 379 (2012), Yu et al. PRB 86, 134421 (2012)] que violam a lei de escala $\\phi= u z$, em que $\\phi$ é o expoente da temperatura crítica, $z$ é o expoente crítico dinâmico e $ u$ é o expoente do comprimento de correlação. Abordamos essa controvérsia numericamente fazendo uma análise de escalonamento finito usando o algoritmo Worm nas suas versões quântica e clássica. Nossos resultados demonstram que trabalhos anteriores sobre a dependência da temperatura de transição superfluido-líquido normal com o potencial químico (ou campo magnético, em sistemas de spin), $T_c \\propto (\\mu-\\mu_c)^\\phi$, estavam equivocados na interpretação de um comportamento transiente na aproximação da região crítica genuína. Quando os parâmetros do modelo são modificados de maneira a ampliar a região crítica quântica, simulações com ambos os modelos clássico e quântico revelam que a lei de escala $\\phi= u z$ [com $\\phi=2.7(2)$, $z=3$ e $ u = 0.88(5)$] é válida. Também estimamos o expoente crítico do parâmetro de ordem, encontrando $\\beta=1.5(2)$.

First Order Phase Transition in a 3D disordered system

We present a detailed numerical study on the effects of adding quenched impurities to a three dimensional system which in the pure case undergoes a strong first order phase transition (specifically, the ferromagnetic/paramagnetic transition of the site-diluted four states Potts model). We can state that the transition remains first-order in the presence of quenched disorder (a small amount of it) but it turns out to be second order as more impurities are added. A tricritical point, which is studied by means of Finite-Size Scaling, separates the first-order and second-order parts of the critical line. The results were made possible by a new definition of the disorder average that avoids the diverging-variance probability distributions that arise using the standard methodology. We also made use of a recently proposed microcanonical Monte Carlo method in which entropy, instead of free energy, is the basic quantity.

Diseño de un modelo geológico-geotécnico 3D de la Vega Baja del Río Segura (Alicante, SE España)

Los modelos geológico-geotécnicos permiten al ingeniero comprender mejor las condiciones reinantes en un determinado lugar, además de identificar los principales problemas geotécnicos y hacer más realista la estimación de propiedades del suelo. En este trabajo se presenta la metodología empleada para el diseño de un modelo geológico-geotécnico tridimensional de la Vega Baja del Río Segura que consta de cuatro zonas caracterizadas por sus propiedades geotécnicas y su problemática asociada. El modelo resulta fundamentalmente de gran utilidad para la planificación de investigaciones preliminares de obras civiles.

Detección automática con snakes y representación 3D sobre imágenes cerebrales

Comunicación presentada en la VI Conferencia de la Asociación Española para la Inteligencia Artificial (CAEPIA'95), Alicante, 15-17 noviembre 1995.

GPGPU implementation of growing neural gas: application to 3D scene reconstruction

Self-organising neural models have the ability to provide a good representation of the input space. In particular the Growing Neural Gas (GNG) is a suitable model because of its flexibility, rapid adaptation and excellent quality of representation. However, this type of learning is time-consuming, especially for high-dimensional input data. Since real applications often work under time constraints, it is necessary to adapt the learning process in order to complete it in a predefined time. This paper proposes a Graphics Processing Unit (GPU) parallel implementation of the GNG with Compute Unified Device Architecture (CUDA). In contrast to existing algorithms, the proposed GPU implementation allows the acceleration of the learning process keeping a good quality of representation. Comparative experiments using iterative, parallel and hybrid implementations are carried out to demonstrate the effectiveness of CUDA implementation. The results show that GNG learning with the proposed implementation achieves a speed-up of 6× compared with the single-threaded CPU implementation. GPU implementation has also been applied to a real application with time constraints: acceleration of 3D scene reconstruction for egomotion, in order to validate the proposal.

3D-based reconstruction using growing neural gas landmark: application to rapid prototyping in shoe last manufacturing

Customizing shoe manufacturing is one of the great challenges in the footwear industry. It is a production model change where design adopts not only the main role, but also the main bottleneck. It is therefore necessary to accelerate this process by improving the accuracy of current methods. Rapid prototyping techniques are based on the reuse of manufactured footwear lasts so that they can be modified with CAD systems leading rapidly to new shoe models. In this work, we present a shoe last fast reconstruction method that fits current design and manufacturing processes. The method is based on the scanning of shoe last obtaining sections and establishing a fixed number of landmarks onto those sections to reconstruct the shoe last 3D surface. Automated landmark extraction is accomplished through the use of the self-organizing network, the growing neural gas (GNG), which is able to topographically map the low dimensionality of the network to the high dimensionality of the contour manifold without requiring a priori knowledge of the input space structure. Moreover, our GNG landmark method is tolerant to noise and eliminates outliers. Our method accelerates up to 12 times the surface reconstruction and filtering processes used by the current shoe last design software. The proposed method offers higher accuracy compared with methods with similar efficiency as voxel grid.

3D Hand Pose Estimation with Neural Networks

We propose the design of a real-time system to recognize and interprethand gestures. The acquisition devices are low cost 3D sensors. 3D hand pose will be segmented, characterized and track using growing neural gas (GNG) structure. The capacity of the system to obtain information with a high degree of freedom allows the encoding of many gestures and a very accurate motion capture. The use of hand pose models combined with motion information provide with GNG permits to deal with the problem of the hand motion representation. A natural interface applied to a virtual mirrorwriting system and to a system to estimate hand pose will be designed to demonstrate the validity of the system.

3D Maps Representation Using GNG

Current RGB-D sensors provide a big amount of valuable information for mobile robotics tasks like 3D map reconstruction, but the storage and processing of the incremental data provided by the different sensors through time quickly become unmanageable. In this work, we focus on 3D maps representation and propose the use of the Growing Neural Gas (GNG) network as a model to represent 3D input data. GNG method is able to represent the input data with a desired amount of neurons or resolution while preserving the topology of the input space. Experiments show how GNG method yields a better input space adaptation than other state-of-the-art 3D map representation methods.

Discontinuity spacing analysis in rock masses using 3D point clouds

The complete characterization of rock masses implies the acquisition of information of both, the materials which compose the rock mass and the discontinuities which divide the outcrop. Recent advances in the use of remote sensing techniques – such as Light Detection and Ranging (LiDAR) – allow the accurate and dense acquisition of 3D information that can be used for the characterization of discontinuities. This work presents a novel methodology which allows the calculation of the normal spacing of persistent and non-persistent discontinuity sets using 3D point cloud datasets considering the three dimensional relationships between clusters. This approach requires that the 3D dataset has been previously classified. This implies that discontinuity sets are previously extracted, every single point is labeled with its corresponding discontinuity set and every exposed planar surface is analytically calculated. Then, for each discontinuity set the method calculates the normal spacing between an exposed plane and its nearest one considering 3D space relationship. This link between planes is obtained calculating for every point its nearest point member of the same discontinuity set, which provides its nearest plane. This allows calculating the normal spacing for every plane. Finally, the normal spacing is calculated as the mean value of all the normal spacings for each discontinuity set. The methodology is validated through three cases of study using synthetic data and 3D laser scanning datasets. The first case illustrates the fundamentals and the performance of the proposed methodology. The second and the third cases of study correspond to two rock slopes for which datasets were acquired using a 3D laser scanner. The second case study has shown that results obtained from the traditional and the proposed approaches are reasonably similar. Nevertheless, a discrepancy between both approaches has been found when the exposed planes members of a discontinuity set were hard to identify and when the planes pairing was difficult to establish during the fieldwork campaign. The third case study also has evidenced that when the number of identified exposed planes is high, the calculated normal spacing using the proposed approach is minor than those using the traditional approach.

μ-MAR: Multiplane 3D Marker based Registration for depth-sensing cameras

Many applications including object reconstruction, robot guidance, and. scene mapping require the registration of multiple views from a scene to generate a complete geometric and appearance model of it. In real situations, transformations between views are unknown and it is necessary to apply expert inference to estimate them. In the last few years, the emergence of low-cost depth-sensing cameras has strengthened the research on this topic, motivating a plethora of new applications. Although they have enough resolution and accuracy for many applications, some situations may not be solved with general state-of-the-art registration methods due to the signal-to-noise ratio (SNR) and the resolution of the data provided. The problem of working with low SNR data, in general terms, may appear in any 3D system, then it is necessary to propose novel solutions in this aspect. In this paper, we propose a method, μ-MAR, able to both coarse and fine register sets of 3D points provided by low-cost depth-sensing cameras, despite it is not restricted to these sensors, into a common coordinate system. The method is able to overcome the noisy data problem by means of using a model-based solution of multiplane registration. Specifically, it iteratively registers 3D markers composed by multiple planes extracted from points of multiple views of the scene. As the markers and the object of interest are static in the scenario, the transformations obtained for the markers are applied to the object in order to reconstruct it. Experiments have been performed using synthetic and real data. The synthetic data allows a qualitative and quantitative evaluation by means of visual inspection and Hausdorff distance respectively. The real data experiments show the performance of the proposal using data acquired by a Primesense Carmine RGB-D sensor. The method has been compared to several state-of-the-art methods. The results show the good performance of the μ-MAR to register objects with high accuracy in presence of noisy data outperforming the existing methods.