we aimed to evaluate clinical, high resolution computed tomography (hrct) and pulmonary function test (pft) findings after 18-23 years of exposure in veterans of sulphur mustard (sm) exposure. we performed a cross-sectional study of 106 patients. inclusion criteria were 1: documented exposure to sm as confirmed by toxicological analysis of their urine and vesicular fluid after exposure 2: singl...

the influence of long-term mixed organic and inorganic contamination on soil microbial activity, community structure and genetic diversity was investigated in soil samples from a coke oven plant located in upper silesia, poland. the tested soils were heavily contaminated with polycyclic aromatic hydrocarbons (pahs) and heavy metals. the microbial communities were characterized using the phospho...

introduction: langerhans cell histiocytosis (lch) is a rare disease characterized by clonal prolifera-tion of histiocytosis in different tissues. permanent consequences (pc) described among subjects with langerhans cell histiocytosis (lch).in this study we report the prevalence of permanent sequel among long – term survivors of lch in our center. methods: we had 30 cases of lch from 1989 – 2001...

Much of the research on long-term potentiation (LTP) is motivated by the question of whether changes in synaptic strength similar to LTP underlie learning and memory. Here we discuss findings from studies on fear conditioning, a form of associative learning whose neural circuitry is relatively well understood, that may be particularly suited for addressing this question. We first review the evi...

B6-Tg/Thy1APP23Sdz (APP23) mutant mice exhibit neurohistological hallmarks of Alzheimer's disease but show intact basal hippocampal neurotransmission and synaptic plasticity. Here, we examine whether spatial learning differently modifies the structural and electrophysiological properties of hippocampal synapses in APP23 and wild-type mice. While no genotypic difference was found in the pseudotr...

Deep neural networks have become the primary learning technique for object recognition. Videos, unlike still images, are temporally coherent which makes the application of deep networks non-trivial. Here, we investigate how motion can aid object recognition in short videos. Our approach is based on Long Short-Term Memory (LSTM) deep networks. Unlike previous applications of LSTMs, we implement ...

Data-driven techniques for interactive narrative generation are the subject of growing interest. Reinforcement learning (RL) offers significant potential for devising data-driven interactive narrative generators that tailor players’ story experiences by inducing policies from player interaction logs. A key open question in RL-based interactive narrative generation is how to model complex player...

Hierarchical control of skilled performance depends on the ability of higher level control to process several lower level units as a single chunk. The present study investigated the development of hierarchical control of skilled typewriting, focusing on the process of memory chunking. In the first 3 experiments, skilled typists typed words or nonwords under concurrent memory load. Memory chunks...

This paper presents reinforcement learning with a Long ShortTerm Memory recurrent neural network: RL-LSTM. Model-free RL-LSTM using Advantage( ) learning and directed exploration can solve non-Markovian tasks with long-term dependencies between relevant events. This is demonstrated in a T-maze task, as well as in a di cult variation of the pole balancing task.