Colombia como referente en la lucha contra las drogas : perspectivas de la cooperación con África Occidental

Este estudio de caso se realiza con el objetivo de analizar cómo la cooperación entre Colombia y África occidental en la lucha contra el tráfico de drogas repercute en la imagen del Estado colombiano como referente en esfuerzos antinarcóticos desde la periferia. En consecuencia, se busca conocer la forma en la cual los acuerdos bilaterales interinstitucionales, la participación en foros y la creación de una agenda internacional de lucha contra las drogas para un escenario nacional transformado, configuran la imagen del Estado colombiano. Para tal objetivo, el trabajo se desarrollará a través de los conceptos de identidad de Alexander Wendt, periferia de Mohammed Ayoob y Cooperación Sur-Sur de la Organización de Naciones Unidas y la Agencia Presidencial de Cooperación Internacional de Colombia.

Papel de la comunidad internacional en la resocialización de niños soldados desvinculados del ejército de resistencia del señor en Uganda (2002-2013)

El objetivo de esta investigación diagnóstica es evaluar las acciones de la Comunidad Internacional en materia de resocialización de niños soldados desvinculados del Ejército de Resistencia del Señor (ERS) en Uganda durante el periodo de 2002 a 2013. Para ello, se hace un análisis de las causas de la existencia de niños soldados, donde se tiene en cuenta la evolución del concepto de la infancia y las particularidades que éste representa en el contexto africano. Así mismo, son analizados los alcances y limitaciones del modelo de asistencia humanitaria para la protección de la niñez enfatizando en los procesos de resocialización brindados a los niños desvinculados del ERS. Esto con el fin de evidenciar las limitaciones de la actuación de la Comunidad Internacional, y brindar una serie de recomendaciones para la implementación de programas de resocialización enfocados en la infancia.

El rol de la Unión Africana (UA) en el Cuerno de África a partir del caso de Somalia - AMISOM (2007-2013)

El propósito de esta monografía es comprender cuál ha sido el rol de la Unión Africana (UA), dentro de la misión de paz AMISOM en el periodo de 2007- 2013. Por ello, el trabajo abarca aspectos geopolíticos e históricos, que han influido en la configuración del conflicto armado de Somalía y que han llevado progresivamente a la creación, evolución e implementación de mecanismos como las misiones de paz. Además, se abarcan los planteamientos del neo-funcionalismo y el neo-regionalismo para comprender las estructuras y las dinámicas propias de la UA y así, comprender la naturaleza tanto de sus acciones, como de sus propósitos; propósitos que aclaman el fomento del panafricanismo. Desde aquí se puede entender como su rol ha contribuido con el crecimiento del mercado de la industria militar en la región, a costa de la responsabilidad de proteger. Por último, se concluye que dichas dinámicas han llevado a la creación de comunidades de inseguridad.

Caracterización sociodemográfica de las enfermedades huérfanas en Colombia

Las enfermedades huérfanas en Colombia, se definen como aquellas crónicamente debilitantes, que amenazan la vida, de baja prevalencia (menor 1/5000) y alta complejidad. Se estima que a nivel mundial existen entre 6000 a 8000 enfermedades raras diferentes(1). Varios países a nivel mundial individual o colectivamente, en los últimos años han creado políticas e incentivos para la investigación y protección de los pacientes con enfermedades raras. Sin embargo, a pesar del creciente número de publicaciones; la información sobre su etiología, fisiología, historia natural y datos epidemiológicos persiste escasa o ausente. Los registros de pacientes, son una valiosa herramienta para la caracterización de las enfermedades, su manejo y desenlaces con o sin tratamiento. Permiten mejorar políticas de salud pública y cuidado del paciente, contribuyendo a mejorar desenlaces sociales, económicos y de calidad de vida. En Colombia, bajo el decreto 1954 de 2012 y las resoluciones 3681 de 2013 y 0430 de 2013 se creó el fundamento legal para la creación de un registro nacional de enfermedades huérfanas. El presente estudio busca determinar la caracterización socio-demográfica y la prevalencia de las enfermedades huérfanas en Colombia en el periodo 2013. Métodos: Se realizó un estudio observacional de corte transversal de fuente secundaria sobre pacientes con enfermedades huérfanas en el territorio nacional; basándose en el registro nacional de enfermedades huérfanas obtenido por el Ministerio de Salud y Protección Social en el periodo 2013 bajo la normativa del decreto 1954 de 2012 y las resoluciones 3681 de 2013 y 0430 de 2013. Las bases de datos obtenidas fueron re-categorizadas en Excel versión 15.17 para la extracción de datos y su análisis estadístico posterior, fue realizado en el paquete estadístico para las ciencias sociales (SPSS v.20, Chicago, IL). Resultados: Se encontraron un total de 13173 pacientes con enfermedades huérfanas para el 2013. De estos, el 53.96% (7132) eran de género femenino y el 46.03% (6083) masculino; la mediana de la edad fue de 28 años con un rango inter-cuartil de 39 años, el 9% de los pacientes presentaron discapacidad. El registro contenía un total de 653 enfermedades huérfanas; el 34% del total de las enfermedades listadas en nuestro país (2). Las patologías más frecuentes fueron el Déficit Congénito del Factor VIII, Miastenia Grave, Enfermedad de Von Willebrand, Estatura Baja por Anomalía de Hormona de Crecimiento y Displasia Broncopulmonar. Discusión: Se estimó que aproximadamente 3.3 millones de colombianos debían tener una enfermedad huérfana para el 2013. El registro nacional logró recolectar datos de 13173 (0.4%). Este bajo número de pacientes, marca un importante sub-registro que se debe al uso de los códigos CIE-10, desconocimiento del personal de salud frente a las enfermedades huérfanas y clasificación errónea de los pacientes. Se encontraron un total de 653 enfermedades, un 34% de las enfermedades reportadas en el listado nacional de enfermedades huérfanas (2) y un 7% del total de enfermedades reportadas en ORPHANET para el periodo 2013 (3). Conclusiones: La recolección de datos y la sensibilización sobre las enfermedades huérfanas al personal de salud, es una estrategia de vital importancia para el diagnóstico temprano, medidas específicas de control e intervenciones de los pacientes. El identificar apropiadamente a los pacientes con este tipo de patologías, permite su ingreso en el registro y por ende mejora el sub-registro de datos. Sin embargo, cabe aclarar que el panorama ideal sería, el uso de un sistema de recolección diferente al CIE-10 y que abarque en mayor medida la totalidad de las enfermedades huérfanas.

Small states and the promotion of their foreign policy agenda in the international scenario: Trinidad and Tobago and the Kyoto Protocol

Este estudio de caso busca identificar los elementos del portafolio de política exterior de Trinidad y Tobago que le permitieron promover exitosamente sus intereses en el Protocolo de Kioto. Al hacer esto, este texto analizará las limitaciones de Trinidad y Tobago en términos de vulnerabilidades de localización, burocracia y recursos. Posteriormente, una revisión del portafolio de política exterior de este Estado ilustrará el uso de estrategias de creación de capacidades y de organización como lo son el contacto con actores institucionales y no gubernamentales, la formación de coaliciones y estrategias argumentativas, entre otras. Finalmente, este artículo concluirá que dichas acciones permitieron la promoción de la agenda de política exterior de Trinidad y Tobago a través de la creación de hojas de ruta y la coordinación de la incertidumbre con el Protocolo de Kioto. Para hacer esto, este trabajo se concentrará en examinar conceptos como vulnerabilidad y priorización, asimismo contrastando diferentes artículos académicos en la materia junto con documentos oficiales de Trinidad y Tobago.

Using linear algebra for protein structural comparison and classification.

In this article, we describe a novel methodology to extract semantic characteristics from protein structures using linear algebra in order to compose structural signature vectors which may be used efficiently to compare and classify protein structures into fold families. These signatures are built from the pattern of hydrophobic intrachain interactions using Singular Value Decomposition (SVD) and Latent Semantic Indexing (LSI) techniques. Considering proteins as documents and contacts as terms, we have built a retrieval system which is able to find conserved contacts in samples of myoglobin fold family and to retrieve these proteins among proteins of varied folds with precision of up to 80%. The classifier is a web tool available at our laboratory website. Users can search for similar chains from a specific PDB, view and compare their contact maps and browse their structures using a JMol plug-in.

Addressing challenges in heterogeneous embedded systems programming: security and performance

Embedded systems are increasingly integral to daily life, improving and facilitating the efficiency of modern Cyber-Physical Systems which provide access to sensor data, and actuators. As modern architectures become increasingly complex and heterogeneous, their optimization becomes a challenging task. Additionally, ensuring platform security is important to avoid harm to individuals and assets. This study primarily addresses challenges in contemporary Embedded Systems, focusing on platform optimization and security enforcement. The initial section of this study delves into the application of machine learning methods to efficiently determine the optimal number of cores for a parallel RISC-V cluster to minimize energy consumption using static source code analysis. Results demonstrate that automated platform configuration is not only viable but also that there is a moderate performance trade-off when relying solely on static features. The second part focuses on addressing the problem of heterogeneous device mapping, which involves assigning tasks to the most suitable computational device in a heterogeneous platform for optimal runtime. The contribution of this section lies in the introduction of novel pre-processing techniques, along with a training framework called Siamese Networks, that enhances the classification performance of DeepLLVM, an advanced approach for task mapping. Importantly, these proposed approaches are independent from the specific deep-learning model used. Finally, this research work focuses on addressing issues concerning the binary exploitation of software running in modern Embedded Systems. It proposes an architecture to implement Control-Flow Integrity in embedded platforms with a Root-of-Trust, aiming to enhance security guarantees with limited hardware modifications. The approach involves enhancing the architecture of a modern RISC-V platform for autonomous vehicles by implementing a side-channel communication mechanism that relays control-flow changes executed by the process running on the host core to the Root-of-Trust. This approach has limited impact on performance and it is effective in enhancing the security of embedded platforms.

An approach to document classification using verb-object pairs

The aim of this thesis is to present a new approach to document classification using verb-object pairs. We explore one possible strategy that uses the presence of relevant verb-object pairs in documents as features and a Naive Bayes classifier as a classifier on which the model is trained. Then, we assess the results from the case study which uses a software based on the strategy and make conclusions.

SynBA: A contextualized Synonim-Based adversarial Attack for text classification

With the advent of high-performance computing devices, deep neural networks have gained a lot of popularity in solving many Natural Language Processing tasks. However, they are also vulnerable to adversarial attacks, which are able to modify the input text in order to mislead the target model. Adversarial attacks are a serious threat to the security of deep neural networks, and they can be used to craft adversarial examples that steer the model towards a wrong decision. In this dissertation, we propose SynBA, a novel contextualized synonym-based adversarial attack for text classification. SynBA is based on the idea of replacing words in the input text with their synonyms, which are selected according to the context of the sentence. We show that SynBA successfully generates adversarial examples that are able to fool the target model with a high success rate. We demonstrate three advantages of this proposed approach: (1) effective - it outperforms state-of-the-art attacks by semantic similarity and perturbation rate, (2) utility-preserving - it preserves semantic content, grammaticality, and correct types classified by humans, and (3) efficient - it performs attacks faster than other methods.

Phylogenetics, Ancestral State Reconstruction, And A New Infrafamilial Classification Of The Pantropical Ochnaceae (medusagynaceae, Ochnaceae S.str., Quiinaceae) Based On Five Dna Regions.

Ochnaceae s.str. (Malpighiales) are a pantropical family of about 500 species and 27 genera of almost exclusively woody plants. Infrafamilial classification and relationships have been controversial partially due to the lack of a robust phylogenetic framework. Including all genera except Indosinia and Perissocarpa and DNA sequence data for five DNA regions (ITS, matK, ndhF, rbcL, trnL-F), we provide for the first time a nearly complete molecular phylogenetic analysis of Ochnaceae s.l. resolving most of the phylogenetic backbone of the family. Based on this, we present a new classification of Ochnaceae s.l., with Medusagynoideae and Quiinoideae included as subfamilies and the former subfamilies Ochnoideae and Sauvagesioideae recognized at the rank of tribe. Our data support a monophyletic Ochneae, but Sauvagesieae in the traditional circumscription is paraphyletic because Testulea emerges as sister to the rest of Ochnoideae, and the next clade shows Luxemburgia+Philacra as sister group to the remaining Ochnoideae. To avoid paraphyly, we classify Luxemburgieae and Testuleeae as new tribes. The African genus Lophira, which has switched between subfamilies (here tribes) in past classifications, emerges as sister to all other Ochneae. Thus, endosperm-free seeds and ovules with partly to completely united integuments (resulting in an apparently single integument) are characters that unite all members of that tribe. The relationships within its largest clade, Ochnineae (former Ochneae), are poorly resolved, but former Ochninae (Brackenridgea, Ochna) are polyphyletic. Within Sauvagesieae, the genus Sauvagesia in its broad circumscription is polyphyletic as Sauvagesia serrata is sister to a clade of Adenarake, Sauvagesia spp., and three other genera. Within Quiinoideae, in contrast to former phylogenetic hypotheses, Lacunaria and Touroulia form a clade that is sister to Quiina. Bayesian ancestral state reconstructions showed that zygomorphic flowers with adaptations to buzz-pollination (poricidal anthers), a syncarpous gynoecium (a near-apocarpous gynoecium evolved independently in Quiinoideae and Ochninae), numerous ovules, septicidal capsules, and winged seeds with endosperm are the ancestral condition in Ochnoideae. Although in some lineages poricidal anthers were lost secondarily, the evolution of poricidal superstructures secured the maintenance of buzz-pollination in some of these genera, indicating a strong selective pressure on keeping that specialized pollination system.

Advancing Bag-of-visual-words Representations For Lesion Classification In Retinal Images.

Diabetic Retinopathy (DR) is a complication of diabetes that can lead to blindness if not readily discovered. Automated screening algorithms have the potential to improve identification of patients who need further medical attention. However, the identification of lesions must be accurate to be useful for clinical application. The bag-of-visual-words (BoVW) algorithm employs a maximum-margin classifier in a flexible framework that is able to detect the most common DR-related lesions such as microaneurysms, cotton-wool spots and hard exudates. BoVW allows to bypass the need for pre- and post-processing of the retinographic images, as well as the need of specific ad hoc techniques for identification of each type of lesion. An extensive evaluation of the BoVW model, using three large retinograph datasets (DR1, DR2 and Messidor) with different resolution and collected by different healthcare personnel, was performed. The results demonstrate that the BoVW classification approach can identify different lesions within an image without having to utilize different algorithms for each lesion reducing processing time and providing a more flexible diagnostic system. Our BoVW scheme is based on sparse low-level feature detection with a Speeded-Up Robust Features (SURF) local descriptor, and mid-level features based on semi-soft coding with max pooling. The best BoVW representation for retinal image classification was an area under the receiver operating characteristic curve (AUC-ROC) of 97.8% (exudates) and 93.5% (red lesions), applying a cross-dataset validation protocol. To assess the accuracy for detecting cases that require referral within one year, the sparse extraction technique associated with semi-soft coding and max pooling obtained an AUC of 94.2 ± 2.0%, outperforming current methods. Those results indicate that, for retinal image classification tasks in clinical practice, BoVW is equal and, in some instances, surpasses results obtained using dense detection (widely believed to be the best choice in many vision problems) for the low-level descriptors.

Hippocampal Dysplasia With Balloon Cells: Case Report And Discussion On Classification.

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Cervical Injuries Scored According To The Subaxial Injury Classification System: An Analysis Of The Literature.

The Subaxial Injury Classification (SLIC) system and severity score has been developed to help surgeons in the decision-making process of treatment of subaxial cervical spine injuries. A detailed description of all potential scored injures of the SLIC is lacking. We performed a systematic review in the PubMed database from 2007 to 2014 to describe the relationship between the scored injuries in the SLIC and their eventual treatment according to the system score. Patients with an SLIC of 1-3 points (conservative treatment) are neurologically intact with the spinous process, laminar or small facet fractures. Patients with compression and burst fractures who are neurologically intact are also treated nonsurgically. Patients with an SLIC of 4 points may have an incomplete spinal cord injury such as a central cord syndrome, compression injuries with incomplete neurologic deficits and burst fractures with complete neurologic deficits. SLIC of 5-10 points includes distraction and rotational injuries, traumatic disc herniation in the setting of a neurological deficit and burst fractures with an incomplete neurologic deficit. The SLIC injury severity score can help surgeons guide fracture treatment. Knowledge of the potential scored injures and their relationships with the SLIC are of paramount importance for spine surgeons who treated subaxial cervical spine injuries.

Validity And Reliability Of A Pediatric Patient Classification Instrument.

to assess the construct validity and reliability of the Pediatric Patient Classification Instrument. correlation study developed at a teaching hospital. The classification involved 227 patients, using the pediatric patient classification instrument. The construct validity was assessed through the factor analysis approach and reliability through internal consistency. the Exploratory Factor Analysis identified three constructs with 67.5% of variance explanation and, in the reliability assessment, the following Cronbach's alpha coefficients were found: 0.92 for the instrument as a whole; 0.88 for the Patient domain; 0.81 for the Family domain; 0.44 for the Therapeutic procedures domain. the instrument evidenced its construct validity and reliability, and these analyses indicate the feasibility of the instrument. The validation of the Pediatric Patient Classification Instrument still represents a challenge, due to its relevance for a closer look at pediatric nursing care and management. Further research should be considered to explore its dimensionality and content validity.

Classification Of Frankfurters By Ft-raman Spectroscopy And Chemometric Methods.

Frankfurters are widely consumed all over the world, and the production requires a wide range of meat and non-meat ingredients. Due to these characteristics, frankfurters are products that can be easily adulterated with lower value meats, and the presence of undeclared species. Adulterations are often still difficult to detect, due the fact that the adulterant components are usually very similar to the authentic product. In this work, FT-Raman spectroscopy was employed as a rapid technique for assessing the quality of frankfurters. Based on information provided by the Raman spectra, a multivariate classification model was developed to identify the frankfurter type. The aim was to study three types of frankfurters (chicken, turkey and mixed meat) according to their Raman spectra, based on the fatty vibrational bands. Classification model was built using partial least square discriminant analysis (PLS-DA) and the performance model was evaluated in terms of sensitivity, specificity, accuracy, efficiency and Matthews's correlation coefficient. The PLS-DA models give sensitivity and specificity values on the test set in the ranges of 88%-100%, showing good performance of the classification models. The work shows the Raman spectroscopy with chemometric tools can be used as an analytical tool in quality control of frankfurters.