An Improved GPU Simulator For Spiking Neural P Systems

Spiking Neural P (SNP) systems, variants of Psystems (under Membrane and Natural computing), are computing models that acquire abstraction and inspiration from the way neurons 'compute' or process information. Similar to other P system variants, SNP systems are Turing complete models that by nature compute non-deterministically and in a maximally parallel manner. P systems usually trade (often exponential) space for (polynomial to constant) time. Due to this nature, P system variants are currently limited to parallel simulations, and several variants have already been simulated in parallel devices. In this paper we present an improved SNP system simulator based on graphics processing units (GPUs). Among other reasons, current GPUs are architectured for massively parallel computations, thus making GPUs very suitable for SNP system simulation. The computing model, hardware/software considerations, and simulation algorithm are presented, as well as the comparisons of the CPU only and CPU-GPU based simulators.Ministerio de Ciencia e Innovación TIN2009–13192Junta de Andalucía P08-TIC-0420

Movies Tags Extraction Using Deep Learning

Retrieving information from movies is becoming increasingly demanding due to the enormous amount of multimedia data generated each day. Not only it helps in efficient search, archiving and classification of movies, but is also instrumental in content censorship and recommendation systems. Extracting key information from a movie and summarizing it in a few tags which best describe the movie presents a dedicated challenge and requires an intelligent approach to automatically analyze the movie. In this paper, we formulate movies tags extraction problem as a machine learning classification problem and train a Convolution Neural Network (CNN) on a carefully constructed tag vocabulary. Our proposed technique first extracts key frames from a movie and applies the trained classifier on the key frames. The predictions from the classifier are assigned scores and are filtered based on their relative strengths to generate a compact set of most relevant key tags. We performed a rigorous subjective evaluation of our proposed technique for a wide variety of movies with different experiments. The evaluation results presented in this paper demonstrate that our proposed approach can efficiently extract the key tags of a movie with a good accuracy

The listening project: a qualitative study on the experiences of pre-registered nurses during the COVID-19 pandemic in Scotland

Background: Due to the rapid increase in the number of COVID-19 infections and deaths, academic institutes worldwide were forced to shift to distance learning. Within the period of global lockdown and isolation, student nurses were one of the groups who faced unique challenges due to the limited practical learning environment caused by the transition to online learning and the emergency hiring of nursing students to fill shortages in many health facilities and help in the COVID-19 response. Aim: To explore the experiences and perceptions of pre-registered nurses in relation to their university education during the COVID-19 pandemic. Methods: Underpinned by Lizzio’s (2011) five senses of student success model, a qualitative approach using peer-to-peer discussion was utilized to explore the experiences of pre-registered nurses during the COVID-19 pandemic. Students who are on their second and final year in the nursing program were invited to participate. Interviews were conducted and transcribed using an online meeting platform. Data were analyzed using the five main stages of framework analysis. Results: Eleven peer-to-peer discussion with 22 students were conducted. The five themes are linked with the five senses student success model: capability, connectedness, purpose, resourcefulness, and culture, which was strongly linked to their satisfaction in their program. Six sub-themes emerged in the data: confidence and learning process under capability, building relationships and communication under connectedness, and student health professional and mental health consequences of COVID-19 pandemic under purpose. Conclusion: The situation was a learning opportunity for the students and the university to further support students and build resilience during a pandemic. It is essential for the university to include concepts of transition, pandemic preparedness, work with practitioners, and provide catch up sessions to analyze gaps on their skills and areas where they need further support

Estudio fisiográfico-sedimentológico de las rías altas del Norte de Lugo

Esta breve comunicación forma parte de una investigación, cuyo conjunto es tema de la tesis doctoral de uno de nosotros (N. T. R.). Se estudian ciertos fenómenos de erosión y sedimentación que tienen lugar en estas rías del litoral cantábrico, a partir de las características morfológicas y de textura que ofrecen los materiales detríticos litorales y continentales en sus márgenes.Estos accidentes geográficos vienen sufriendo un acentuado fenómeno de relleno por materiales procedentes del mar de tipo arenoso y de tierra, de carácter térreo-fangoso ; tal proceso de relleno se ha acentuado a medida que se han desarrollado las marismas, junqueras y bajos de arena, de tal modo, que actualmente el acceso a las zonas interiores portuarias se hace con dificultad. La deposición de sedimentos es debida al desequilibrio existente entre los aportes de materiales procedentes del mar y de tierra y el poder de arrastre del juego de mareas y corrientes en el ámbito de las rías. En consecuencia, el tema es de gran interés no sólo desde el punto de vista de la investigación científica, sino también utilitario de tipo  técnico, puesto que plantea problemas relacionados con el acceso a zonas portuarias a lo largo de vías de comunicación marítima

Uncovering allosteric pathways in caspase-1 with Markov transient analysis and multiscale community detection

Allosteric regulation at distant sites is central to many cellular processes. In particular, allosteric sites in proteins are a major target to increase the range and selectivity of new drugs, and there is a need for methods capable of identifying intra-molecular signalling pathways leading to allosteric effects. Here, we use an atomistic graph-theoretical approach that exploits Markov transients to extract such pathways and exemplify our results in an important allosteric protein, caspase-1. Firstly, we use Markov Stability community detection to perform a multiscale analysis of the structure of caspase-1 which reveals that the active conformation has a weaker, less compartmentalised large-scale structure as compared to the inactive conformation, resulting in greater intra-protein coherence and signal propagation. We also carry out a full computational point mutagenesis and identify that only a few residues are critical to such structural coherence. Secondly, we characterise explicitly the transients of random walks originating at the active site and predict the location of a known allosteric site in this protein quantifying the contribution of individual bonds to the communication pathway between the active and allosteric sites. Several of the bonds we find have been shown experimentally to be functionally critical, but we also predict a number of as yet unidentified bonds which may contribute to the pathway. Our approach offers a computationally inexpensive method for the identification of allosteric sites and communication pathways in proteins using a fully atomistic description.Comment: 14 pages, 8 figure

When Matrices Meet Brains

Spiking neural P systems (SN P systems, for short) are a class of distributed parallel computing devices inspired from the way neurons communicate by means of spikes. In this work, a discrete structure representation of SN P systems is proposed. Specifically, matrices are used to represent SN P systems. In order to represent the computations of SN P systems by matrices, configuration vectors are defined to monitor the number of spikes in each neuron at any given configuration; transition net gain vectors are also introduced to quantify the total amount of spikes consumed and produced after the chosen rules are applied. Nondeterminism of the systems is assured by a set of spiking transition vectors that could be used at any given time during the computation. With such matrix representation, it is quite convenient to determine the next configuration from a given configuration, since it involves only multiplying vectors to a matrix and adding vectors

A Spiking Neural P System Simulator Based on CUDA

In this paper we present a Spiking Neural P system (SNP system) simulator based on graphics processing units (GPUs). In particular we implement the simulator using NVIDIA CUDA enabled GPUs. The massively parallel architecture of current GPUs is very suitable for the maximally parallel computations of SNP systems. We simulate a wider variety of SNP systems, after presenting a previous work on SNP system matrix representation which led to their simulation in GPUs, and the simulation algorithm included here. Finally, we compare and present the performance speedups of the CPU-GPU based simulator over the CPU only simulator.Ministerio de Ciencia e Innovación TIN2009–13192Junta de Andalucía P08-TIC-0420

Impact of Region-of-Interest Delineation Methods, Reconstruction Algorithms, and Intra- and Inter-Operator Variability on Internal Dosimetry Estimates Using PET

Purpose: Human dosimetry studies play a central role in radioligand development for positron emission tomography (PET). Drawing regions of interest (ROIs) on the PET images is used to measure the dose in each organ. In the study aspects related to ROI delineation methods were evaluated for two radioligands of different biodistribution (intestinal vs urinary). Procedures: PET images were simulated from a human voxel-based phantom. Several ROI delineation methods were tested: antero-posterior projections (AP), 3D sub-samples of the organs (S), and a 3D volume covering the whole-organ (W). Inter- and intra-operator variability ROI drawing was evaluated by using human data. Results: The effective dose estimates using S and W methods were comparable to the true values. AP methods overestimated (49 %) the dose for the radioligand with intestinal biodistribution. Moreover, the AP method showed the highest inter-operator variability: 11 ± 1 %. Conclusions: The sub-sampled organ method showed the best balance between quantitative accuracy and inter- and intra-operator variability