El algoritmo HyRPNI y una aplicación en bioinformática

Proponemos un algoritmo de inferencia gramatical para lenguajes regulares que permite ahorrar cómputo al usar dos criterios diferentes para elegir los estados a ser procesados, un criterio se usa en la primera fase del proceso de inferencia (al principio) y el otro en el resto del proceso. Realizamos experimentos para observar el desempeño del algoritmo, para aprender sobre el tamaño ideal de su primera fase y para mostrar su aplicación en la solución de un problema específico en bioinformática: la predicción de sitios de corte en poliproteínas codificadas por virus de la familia Potyviridae./ We propose a grammar inference algorithm for regular languages which saves computational cost by using two different criteria to choose states to be processed: one in the first phase of the inference process (the beginning) and another for the rest of the process. We applied experiments to observe performance of the algorithm, to learn about the best size of its first phase and to show results of its application to solve a specific problem in Bioinformatics: the cleavage site prediction problem in polyproteins encoded by viruses of the Potyviridae family

Area-based conservation: Taking stock and looking ahead

Area-based conservation, particularly of protected areas, is the primary approach used globally to address biodiversity decline and currently covers 8% of the world's oceans and 17% of its lands. In the wake of the adoption of the Kunming-Montreal Global Biodiversity Framework under the Convention on Biological Diversity, area-based conservation (including protected areas and other effective area-based conservation measures [OECMs]) is set to diversify and rapidly expand as mandated by the 30x30 target to protect 30% of the planet by 2030. At this pivotal point, we take stock of the approach, including its history in global conservation policy and performance to date. We outline the following priority directions to ensure area-based conservation contributes to securing a sustainable and just future: (1) embracing a diverse area-based conservation toolbox to stem biodiversity loss, (2) centering social equity in area-based conservation, and (3) adopting robust monitoring and review processes to ensure effective and equitable outcomes

Soft Masking for Cost-Constrained Channel Pruning

Structured channel pruning has been shown to significantly accelerate inference time for convolution neural networks (CNNs) on modern hardware, with a relatively minor loss of network accuracy. Recent works permanently zero these channels during training, which we observe to significantly hamper final accuracy, particularly as the fraction of the network being pruned increases. We propose Soft Masking for cost-constrained Channel Pruning (SMCP) to allow pruned channels to adaptively return to the network while simultaneously pruning towards a target cost constraint. By adding a soft mask re-parameterization of the weights and channel pruning from the perspective of removing input channels, we allow gradient updates to previously pruned channels and the opportunity for the channels to later return to the network. We then formulate input channel pruning as a global resource allocation problem. Our method outperforms prior works on both the ImageNet classification and PASCAL VOC detection datasets.Comment: Accepted by ECCV 202

Stress compensation by gap monolayers for stacked InAs/GaAs quantum dots solar cells

In this work we report the stacking of 10 and 50 InAs quantum dots layers using 2 monolayers of GaP for stress compensation and a stack period of 18 nm on GaAs (001) substrates. Very good structural and optical quality is found in both samples. Vertical alignment of the dots is observed by transmission electron microscopy suggesting the existence of residual stress around them. Photocurrent measurements show light absorption up to 1.2 μm in the nanostructures together with a reduction in the blue response of the device. As a result of the phosphorus incorporation in the barriers, a very high thermal activation energy (431 meV) has also been obtained for the quantum dot emission

Complicaciones tras la artrotomía en el tratamiento de las fracturas desplazadas del cuello del radio en la infancia

Presentamos un estudio retrospectivo de los resultados obtenidos en una serie de 14 fracturas del cuello del radio desplazadas con más de 30º de inclinación (Judet grados 3 y 4) en niños entre 7 y 14 años tratados mediante artrotomía y fijación con agujas. La distribución por sexos fue de 9 niñas y 5 niños. El seguimiento medio fue de 47 meses. Cabe destacar que no hemos encontrado relación entre el retraso en el tratamiento quirúrgico y los resultados funcionales. Por otro lado, sí aparece una relación entre la angulación residual de la cabeza del radio y peores resultados funcionales.We report the retrospective results of 14 displaced radial neck fractures with >30ºof tilt (Judet grades 3-4) in children aged between 7 and 14 years treated with arthrotomy and pinning. Sex distribution was 9 girl and 5 boys. The average follow-up was 47 months. We found no relationship between delay in the surgical treatment and functional results. On the other hand, a relationship between residual final tilt and poorer functional results appears

Optimizing Perioperative Decision Making: Improved Information for Clinical Workflow Planning

Perioperative care is complex and involves multiple interconnected subsystems. Delayed starts, prolonged cases and overtime are common. Surgical procedures account for 40–70% of hospital revenues and 30–40% of total costs. Most planning and scheduling in healthcare is done without modern planning tools, which have potential for improving access by assisting in operations planning support. We identified key planning scenarios of interest to perioperative leaders, in order to examine the feasibility of applying combinatorial optimization software solving some of those planning issues in the operative setting. Perioperative leaders desire a broad range of tools for planning and assessing alternate solutions. Our modeled solutions generated feasible solutions that varied as expected, based on resource and policy assumptions and found better utilization of scarce resources. Combinatorial optimization modeling can effectively evaluate alternatives to support key decisions for planning clinical workflow and improving care efficiency and satisfaction