Comment on the Case of Haggerty v. Sherbourne Mercantile Co. et. al.

Comment on the Case of Haggerty v. Sherbourne Mercantile Co. et. al

Skeletonization of sparse shapes using dynamic competitive neural networks

La detección de regiones y objetos en imágenes digitales es un tema de suma importancia en la resolución de numerosos problemas correspondientes al área de reconocimiento de patrones. En esta dirección los algoritmos de esqueletización son una herramienta muy utilizada ya que permiten reducir la cantidad de información disponible facilitando la extracción de características para su posterior reconocimiento y clasificación. Además, esta transformación de la información original en sus características esenciales, facilita la eliminación de ruidos locales presentes en la entrada de datos. Este artículo propone una nueva estrategia de esqueletización aplicable a imágenes esparcidas a partir de una red neuronal competitiva dinámica entrenada con el método AVGSOM. La estrategia desarrollada en este trabajo determina los arcos que forman el esqueleto combinando el aprendizaje no supervisado del AVGSOM con un árbol de dispersión mínima (minimun spaning tree). El método propuesto ha sido aplicado en imágenes con diferente forma y grado de dispersión. En particular, los resultados obtenidos han sido comparados con soluciones existentes mostrando resultados satisfactorios. Finalmente se presentan algunas conclusiones así como algunas líneas de trabajo futurasThe detection of regions and objects in digital images is a topic of utmost importance for solving several problems related to the area of pattern recognition. In this direction, skeletonization algorithms are a widely used tool since they allow us to reduce the quantity of available data, easing the detection of characteristics for their recognition and classification. In addition, this transformation of the original data in its essential characteristics eases the elimination of local noise which is present in the data input. This paper proposes a new skeletonization strategy applicable to sparse images from a competitive, dynamic neural network trained with the AVGSOM method. The strategy developed in this paper determines the arc making up the skeleton combining AVGSOM non-supervised learning with a minimum spanning tree. The proposed method has been applied in images with different spanning shape and degree. In particular, the results obtained have been compared to existing solutions, showing successful results. Finally, some conclusions, together with some future lines of work, are presented.VII Workshop de Agentes y Sistemas Inteligentes (WASI)Red de Universidades con Carreras en Informática (RedUNCI

Pain and temperature processing in dementia: a clinical and neuroanatomical analysis

Symptoms suggesting altered processing of pain and temperature have been described in dementia diseases and may contribute importantly to clinical phenotypes, particularly in the frontotemporal lobar degeneration spectrum, but the basis for these symptoms has not been characterized in detail. Here we analysed pain and temperature symptoms using a semi-structured caregiver questionnaire recording altered behavioural responsiveness to pain or temperature for a cohort of patients with frontotemporal lobar degeneration (n = 58, 25 female, aged 52–84 years, representing the major clinical syndromes and representative pathogenic mutations in the C9orf72 and MAPT genes) and a comparison cohort of patients with amnestic Alzheimer’s disease (n = 20, eight female, aged 53–74 years). Neuroanatomical associations were assessed using blinded visual rating and voxel-based morphometry of patients’ brain magnetic resonance images. Certain syndromic signatures were identified: pain and temperature symptoms were particularly prevalent in behavioural variant frontotemporal dementia (71% of cases) and semantic dementia (65% of cases) and in association with C9orf72 mutations (6/6 cases), but also developed in Alzheimer’s disease (45% of cases) and progressive non-fluent aphasia (25% of cases). While altered temperature responsiveness was more common than altered pain responsiveness across syndromes, blunted responsiveness to pain and temperature was particularly associated with behavioural variant frontotemporal dementia (40% of symptomatic cases) and heightened responsiveness with semantic dementia (73% of symptomatic cases) and Alzheimer’s disease (78% of symptomatic cases). In the voxel-based morphometry analysis of the frontotemporal lobar degeneration cohort, pain and temperature symptoms were associated with grey matter loss in a right-lateralized network including insula (P < 0.05 corrected for multiple voxel-wise comparisons within the prespecified anatomical region of interest) and anterior temporal cortex (P < 0.001 uncorrected over whole brain) previously implicated in processing homeostatic signals. Pain and temperature symptoms accompanying C9orf72 mutations were specifically associated with posterior thalamic atrophy (P < 0.05 corrected for multiple voxel-wise comparisons within the prespecified anatomical region of interest). Together the findings suggest candidate cognitive and neuroanatomical bases for these salient but under-appreciated phenotypic features of the dementias, with wider implications for the homeostatic pathophysiology and clinical management of neurodegenerative diseases

Skeletonization of sparse shapes using dynamic competitive neural networks

La detección de regiones y objetos en imágenes digitales es un tema de suma importancia en la resolución de numerosos problemas correspondientes al área de reconocimiento de patrones. En esta dirección los algoritmos de esqueletización son una herramienta muy utilizada ya que permiten reducir la cantidad de información disponible facilitando la extracción de características para su posterior reconocimiento y clasificación. Además, esta transformación de la información original en sus características esenciales, facilita la eliminación de ruidos locales presentes en la entrada de datos. Este artículo propone una nueva estrategia de esqueletización aplicable a imágenes esparcidas a partir de una red neuronal competitiva dinámica entrenada con el método AVGSOM. La estrategia desarrollada en este trabajo determina los arcos que forman el esqueleto combinando el aprendizaje no supervisado del AVGSOM con un árbol de dispersión mínima (minimun spaning tree). El método propuesto ha sido aplicado en imágenes con diferente forma y grado de dispersión. En particular, los resultados obtenidos han sido comparados con soluciones existentes mostrando resultados satisfactorios. Finalmente se presentan algunas conclusiones así como algunas líneas de trabajo futurasThe detection of regions and objects in digital images is a topic of utmost importance for solving several problems related to the area of pattern recognition. In this direction, skeletonization algorithms are a widely used tool since they allow us to reduce the quantity of available data, easing the detection of characteristics for their recognition and classification. In addition, this transformation of the original data in its essential characteristics eases the elimination of local noise which is present in the data input. This paper proposes a new skeletonization strategy applicable to sparse images from a competitive, dynamic neural network trained with the AVGSOM method. The strategy developed in this paper determines the arc making up the skeleton combining AVGSOM non-supervised learning with a minimum spanning tree. The proposed method has been applied in images with different spanning shape and degree. In particular, the results obtained have been compared to existing solutions, showing successful results. Finally, some conclusions, together with some future lines of work, are presented.VII Workshop de Agentes y Sistemas Inteligentes (WASI)Red de Universidades con Carreras en Informática (RedUNCI

Skeletonization of sparse shapes using dynamic competitive neural networks

The detection of regions and objects in digital images is a topic of utmost importance for solving several problems related to the area of pattern recognition. In this direction, skeletonization algorithms are a widely used tool since they allow us to reduce the quantity of available data, easing the detection of characteristics for their recognition and classification. In addition, this transformation of the original data in its essential characteristics eases the elimination of local noise which is present in the data input. This paper proposes a new skeletonization strategy applicable to sparse images from a competitive, dynamic neural network trained with the AVGSOM method. The strategy developed in this paper determines the arc making up the skeleton combining AVGSOM non-supervised learning with a minimum spanning tree. The proposed method has been applied in images with different spanning shape and degree. In particular, the results obtained have been compared to existing solutions, showing successful results. Finally, some conclusions, together with some future lines of work, are presented.Facultad de Informátic

Plan de negocios para evaluar la viabilidad de implementar proyectos agr?colas para propietarios de terrenos en los valles de Santa Eulalia y Calango

El presente plan de negocios desarrolla la propuesta de una empresa que ofrece servicios de formulaci?n y gesti?n de proyectos agr?colas de peque?a y mediana escala en los valles de Santa Eulalia y Calango, para propietarios de terrenos agr?colas en estas zonas, con un horizonte de evaluaci?n de 5 a?os. El proyecto fue motivado por la potencial escalabilidad del modelo de negocio y su contribuci?n social para otros valles del Per?. Se aborda la problem?tica de poca tecnificaci?n de los campos, desconfianza de los inversionistas, poca capacidad de negociaci?n, ausencia del Estado y dificultades de acceso a financiamientos, que resultan en una baja rentabilidad de la comercializaci?n de los productos agr?colas. La propuesta de negocio, denominado ?Agrobusiness?, presenta una oferta business to business (B2B), que ofrece los servicios de perfil, formulaci?n y gesti?n de proyectos para el sector agr?cola de peque?a y mediana escala. Agrobusiness se caracteriza por la generaci?n de confianza, la comunicaci?n sencilla e inclusiva y la personalizaci?n de los servicios. El estudio determin? que un 90% de los encuestados est?n interesados en los servicios del negocio y un 72% a pagar por lo menos 20% de la utilidad neta de los proyectos formulados

Towards the Construction of Expressed Proteomes Using a Leishmania tarentolae Based Cell-Free Expression System

The adaptation of organisms to a parasitic life style is often accompanied by the emergence of novel biochemical pathways absent in free-living organisms. As a result, the genomes of specialized parasitic organisms often code for a large number (>50%) of proteins with no detectable homology or predictable function. Although understanding the biochemical properties of these proteins and their roles in parasite biogenesis is the next challenge of molecular parasitology, analysis tools developed for free-living organisms are often inadequate for this purpose. Here we attempt to solve some of these problems by developing a methodology for the rapid production of expressed proteomes in cell-free systems based on parasitic organisms. To do so we take advantage of Species Independent Translational Sequences (SITS), which can efficiently mediate translation initiation in any organism. Using these sequences we developed a single-tube in vitro translation system based on the parasitic protozoan Leishmania tarentolae. We demonstrate that the system can be primed directly with SITS containing templates constructed by overlap extension PCR. To test the systems we simultaneously amplified 31 of L. tarentolae's putative translation initiation factors and phosphatases directly from the genomic DNA and subjected them to expression, purification and activity analysis. All of the amplified products produced soluble recombinant proteins, and putative phosphatases could be purified to at least 50% purity in one step. We further compared the ability of L. tarentolae and E. coli based cell-free systems to express a set of mammalian, L. tarentolae and Plasmodium falciparum Rab GTPases in functional form. We demonstrate that the L. tarentolae cell-free system consistently produced higher quality proteins than E. coli-based system. The differences were particularly pronounced in the case of open reading frames derived from P. falciparum. The implications of these developments are discussed

A preliminary assessment of the effects of ATI-2042 in subjects with paroxysmal atrial fibrillation using implanted pacemaker methodology

Aims ATI-2042 (budiodarone) is a chemical analogue of amiodarone with a half life of 7 h. It is electrophysiologically similar to amiodarone, but may not have metabolic and interaction side effects. The sophisticated electrocardiograph logs of advanced DDDRP pacemakers were used to monitor the efficacy of ATI-2042. The aim of this study was to determine the preliminary efficacy and safety of ATI-2042 in patients with paroxsymal atrial fibrillation (PAF) and pacemakers. Methods and results Six women with AF burden (AFB) between 1 and 50% underwent six sequential 2-week study periods. Patients received 200 mg bid of ATI-2042 during Period 2 (p2), 400 mg bid during p3, 600 mg bid during p4, 800 mg bid during p5, and no drug during baseline and washout (p1 and p6). Pacemaker data for the primary outcome measure AFB were downloaded during each period. Mean AFB decreased between baseline and all doses: AFB at baseline (SD) was 20.3 ± 14.6% and mean AFB at 200 mg bid was 5.2 ± 4.2%, at 400 mg bid 5.2 ± 5.2%, at 600 mg bid 2.8 ± 3.4%, and at 800 mg bid 1.5 ± 0.5%. The mean reductions in AFB at all doses of ATI-2042 were statistically significant (P < 0.005). Atrial fibrillation burden increased in washout. Atrial fibrillation episodes tended to increase with ATI-2042, but this was offset by substantial decreases in episode duration. ATI-2042 was generally well tolerated. Conclusion ATI-2042 effectively reduced AFB over all doses studied by reducing mean episode duration. A large-scale study will be required to confirm this effect