Gaussian processes for POMDP-based dialogue manager optimization

A partially observable Markov decision process (POMDP) has been proposed as a dialog model that enables automatic optimization of the dialog policy and provides robustness to speech understanding errors. Various approximations allow such a model to be used for building real-world dialog systems. However, they require a large number of dialogs to train the dialog policy and hence they typically rely on the availability of a user simulator. They also require significant designer effort to hand-craft the policy representation. We investigate the use of Gaussian processes (GPs) in policy modeling to overcome these problems. We show that GP policy optimization can be implemented for a real world POMDP dialog manager, and in particular: 1) we examine different formulations of a GP policy to minimize variability in the learning process; 2) we find that the use of GP increases the learning rate by an order of magnitude thereby allowing learning by direct interaction with human users; and 3) we demonstrate that designer effort can be substantially reduced by basing the policy directly on the full belief space thereby avoiding ad hoc feature space modeling. Overall, the GP approach represents an important step forward towards fully automatic dialog policy optimization in real world systems.This is the accepted manuscript version of an article first published in IEEE/ACM Transactions on Audio, Speech, and Language Processing. The final published version is available online from IEEE at http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6601004. © 2013 IEEE

Stochastic Language Generation in Dialogue using Recurrent Neural Networks with Convolutional Sentence Reranking

The natural language generation (NLG) component of a spoken dialogue system (SDS) usually needs a substantial amount of handcrafting or a well-labeled dataset to be trained on. These limitations add significantly to development costs and make cross-domain, multi-lingual dialogue systems intractable. Moreover, human languages are context-aware. The most natural response should be directly learned from data rather than depending on predefined syntaxes or rules. This paper presents a statistical language generator based on a joint recurrent and convolutional neural network structure which can be trained on dialogue act-utterance pairs without any semantic alignments or predefined grammar trees. Objective metrics suggest that this new model outperforms previous methods under the same experimental conditions. Results of an evaluation by human judges indicate that it produces not only high quality but linguistically varied utterances which are preferred compared to n-gram and rule-based systems.Comment: To be appear in SigDial 201

Efekti aspirina na apoptozu neutrofilnih granulocita

Neutrophils are a part of the immune system, and they are involved in host defence against microorganisms. Neutrophil granulocytes have the shortest lifespan among leukocytes, which can be modulated by cytokines and pharmacological agents. The effect of aspirin on apoptosis of inflammatory granulocytes has not been studied in detail yet, and therefore was the chosen subject of this study. Inflammatory granulocytes have been isolated from polyvinyl sponges implanted under the skin of Albino Oxford (AO) rats. Inflammatory cells that were isolated 20 hours later were more than 95% neutrophil granulocytes. The cells were cultivated 24 h with different concentrations of aspirin ranging from 1 µM to 10 mM. After the cultivation period, apoptosis of neutrophils was assessed by morphological criteria, as well as by flow cytometry (after staining the cells with propidium iodide). We found that at concentrations from 0,1 mM to 2,5 mM aspirin inhibited apoptosis of granulocytes, but at 10 mM aspirin induced apoptosis of these cells.Neutrofilni granulociti su deo imunog sistema, uključenog u odbranu od mikroorganizama. Oni imaju najkraći životni vek među leukocitima, koji se može modulisati citokinima i farmakološkim agensima, a do sada nije ispitivan efekat aspirina na apoptozu inflamatornih granulocita. Zbog toga je u ovoj studiji ispitivan efekat aspirina na apoptozu inflamatornih neutrofilnih granulocita pacova. Inflamatorni granulociti su izolovani iz polivinilskih sunđera, potkožno implantiranih, pacovima Albino Oxford (AO) soja. Inflamatorne ćelije, izolovane 20 sati kasnije, najvećim delom (više od 95 %) predstavljaju neutrofilne granulocite. Ove ćelije su kultivisane 24 sata sa aspirinom u koncentracijama od 1 µM do 10 mM. Posle ovog perioda supernatanti su sakupljani i korišćeni za merenje koncentracije NO. Ćelije su bojene propidijum jodidom i apoptoza je analizirana na protočnom citofluorimetru, kao i pomoću morfoloških kriterijuma. Ustanovljeno je da u koncentracijama od 0,1 do 2,5 mM aspirin inhibira, a samo u visokim koncentracijama (10 mM) indukuje apoptozu ovih ćelija. Aspirinom indukovana apoptoza je bila u pozitivnoj korelaciji sa smanjenom produkcijom NO

Dialogue manager domain adaptation using Gaussian process reinforcement learning

Spoken dialogue systems allow humans to interact with machines using natural speech. As such, they have many benefits. By using speech as the primary communication medium, a computer interface can facilitate swift, human-like acquisition of information. In recent years, speech interfaces have become ever more popular, as is evident from the rise of personal assistants such as Siri, Google Now, Cortana and Amazon Alexa. Recently, data-driven machine learning methods have been applied to dialogue modelling and the results achieved for limited-domain applications are comparable to or outperform traditional approaches. Methods based on Gaussian processes are particularly effective as they enable good models to be estimated from limited training data. Furthermore, they provide an explicit estimate of the uncertainty which is particularly useful for reinforcement learning. This article explores the additional steps that are necessary to extend these methods to model multiple dialogue domains. We show that Gaussian process reinforcement learning is an elegant framework that naturally supports a range of methods, including prior knowledge, Bayesian committee machines and multi-agent learning, for facilitating extensible and adaptable dialogue systems.Engineering and Physical Sciences Research Council (Grant ID: EP/M018946/1 ”Open Domain Statistical Spoken Dialogue Systems”

Multi-domain neural network language generation for spoken dialogue systems

Moving from limited-domain natural language generation (NLG) to open domain is difficult because the number of semantic input combinations grows exponentially with the number of domains. Therefore, it is important to leverage existing resources and exploit similarities between domains to facilitate domain adaptation. In this paper, we propose a procedure to train multi-domain, Recurrent Neural Network-based (RNN) language generators via multiple adaptation steps. In this procedure, a model is first trained on counterfeited data synthesised from an out-of-domain dataset, and then fine tuned on a small set of in-domain utterances with a discriminative objective function. Corpus-based evaluation results show that the proposed procedure can achieve competitive performance in terms of BLEU score and slot error rate while significantly reducing the data needed to train generators in new, unseen domains. In subjective testing, human judges confirm that the procedure greatly improves generator performance when only a small amount of data is available in the domain.Toshiba Research Europe Ltd.This is the accepted manuscript. It is currently embargoed pending publication

Supplementary data for article: Banjanac, T.; Dragićević, M.; Šiler, B.; Gašić, U.; Bohanec, B.; Nestorović Živković, J.; Trifunović, S.; Mišić, D. Chemodiversity of Two Closely Related Tetraploid Centaurium Species and Their Hexaploid Hybrid: Metabolomic Search for High-Resolution Taxonomic Classifiers. Phytochemistry 2017, 140, 27–44. https://doi.org/10.1016/j.phytochem.2017.04.005

Supplementary material for: [https://doi.org/10.1016/j.phytochem.2017.04.005]Related to published version: [http://cherry.chem.bg.ac.rs/handle/123456789/2477

Results of otoplasty by scoring anterior surface of auricular cartilage

A prominent ear, so called a protruding or 'lop' ear, is the most common congenital deformity of the external ear. This deformity persists when the mastoid-helix angle (MHA) is higher than 30 degrees. It is relatively common among the population with the incidence of about 5%. The aim of this study is to present surgical procedure and our results using otoplasty with scoring anterior surface of the auricular cartilage. To analyze objective and subjective surgical procedure effects. Between 2011 and 2014 we treated 28 patients. We found statistically high significance p<0.01 in value mastoid-helix angle (MHA) preoperative and postoperative. In patients with bilateral otoplasty the difference between left and right MHAs after surgical procedure is less than 4 degrees. The difference of head-helix distance (HHD) preoperative and postoperative is statistically important with high significance p<0.05. Preoperative satisfaction by personal appearance was better after surgical procedure p<0.05. Complications occurred in 9 cases (32.4%). Otoplasty by scoring anterior surface of auricular cartilage is safe procedure for correction of prominent ear with excellent results on patient satisfaction by personal appearance. Effect of reducing the MHA and HHD is long lasting

In vitro digestion of meat- and cereal-based food matrix enriched with grape extracts: How are polyphenol composition, bioaccessibility and antioxidant activity affected?

The aim of this study was to evaluate the effect of enriching a complex food matrix (FM) with grape extracts on polyphenol content, composition, bioaccessibility and antioxidant activity during digestion. The grape extracts and FM were separately tested under the same conditions as controls. The FM by itself contains a significant amount of phenolic acids and flavonols, influencing the final recovery of polyphenols from grape extracts. The FM significantly increased the total recovery of polyphenols after digestion of grape seed extracts compared to those digested without the FM; however, a low recovery of proantocyanidins and total flavonoids was observed. Digestive fluids and FM compounds significantly increased the total polyphenol content of grape digests and significantly contributed to their ABTS(center dot+) scavenging activity and ferrous-ion-chelating capacity. The present study suggested that enrichment of meat-and cereal-based products with grape polyphenol extracts could be a good strategy to formulate a healthier diet

The Role of C-Fos Protein, Somatostatin and Neuropeptide Y in the Pathogenesis of Ischemic Brain Injuries Based on Animal Model of Cerebral Ischemia

The aim of this study was to define all the areas of changes in expression of nuclear c-Fos protein (c-Fos), cytoplasmic somatostatin (SS) and neuropeptide Y (NPY) in rat brain during experimental ischemia. Using the immunohistoche- mical method, brain mapping (based on the atlas by Paxinos & Watson) of immunoreactivity for c-Fos, SS and NPY in 39 rats, was studied in telencephalon, diencephalon and midbrain after resistant and transitory ischemia. The first ex- perimental group (R group) was exposed to resistant ischemia by occlusion (10 minutes) of four vessels according to the Pulsinelli method. The second group was first exposed to transitory (4 minutes) ischemia (preconditioning) and, after 72 hours, to total ischemia as in the R group. There was a statistical difference between the R and T group in the c-Fos reac- tion, especially in the parietofrontal cortex, anterior amygdaloid area, claustrum, reuniens nucleus and suprachiasmatic nucleus. The dominant immunohistochemical reactivity was found for c-Fos protein, and the most reactive in terms of co-localization of c-Fos with SS and NPY was periventricular area of hypothalamus. The mapping showed that both, phylogenetically new as well as phylogenetically older brain structures reacted immunohistochemically. The results of our study, regarding the impact of preconditioning with a short period of ischemia on c-Fos activity and co-localization of c-Fos with SS and NPY immunoreactivity, showed the need for future studies of brain neuropeptides related to re- gional and time effects, and indicated brain structures which may require pharmacological targeting to achieve neuro- protective level of proto-oncogene activity in populations at risk

New perspectives of purple starthistle (Centaurea calcitrapa) leaf extracts: phytochemical analysis, cytotoxicity and antimicrobial activity

Ethnobotanical and ethnopharmacological studies of many Centaurea species indicated their potential in folk medicine so far. However, investigations of different Centaurea calcitrapa L. extracts in terms of cytotoxicity and antimicrobial activity against phytopathogens are generally scarce. The phenolic profile and broad antimicrobial activity (especially towards bacterial phytopathogens) of methanol (MeOH), 70% ethanol (EtOH), ethyl-acetate (EtOAc), 50% acetone (Me2CO) and dichloromethane: methanol (DCM: MeOH, 1: 1) extracts of C. calcitrapa leaves and their potential toxicity on MRC-5 cell line were investigated for the first time. A total of 55 phenolic compounds were identified: 30 phenolic acids and their derivatives, 25 flavonoid glycosides and aglycones. This is also the first report of the presence of centaureidin, jaceidin, kaempferide, nepetin, flavonoid glycosides, phenolic acids and their esters in C. calcitrapa extracts. The best results were obtained with EtOAc extract with lowest MIC values expressed in µg/mL ranging from 13 to 25, while methicillin resistant Staphylococcus aureus was the most susceptible strain. The most susceptible phytopathogens were Pseudomonas syringae pv. syringae, Xanthomonas campestris pv. campestris and Agrobacterium tumefaciens. The highest cytotoxicity was recorded for EtOAc and Me2CO extracts with the lowest relative and absolute IC50 values between 88 and 102 µg/mL, while EtOH extract was the least toxic with predicted relative IC50 value of 1578 µg/mL. Our results indicate that all tested extracts at concentration considered as non-toxic can be one of great importance in combat towards phytopathogenic and human pathogenic strains, as well as natural sources of antimicrobials