Neural-symbolic computing: An effective methodology for principled integration of machine learning and reasoning

Current advances in Artificial Intelligence and machine learning in general, and deep learning in particular have reached unprecedented impact not only across research communities, but also over popular media channels. However, concerns about interpretability and accountability of AI have been raised by influential thinkers. In spite of the recent impact of AI, several works have identified the need for principled knowledge representation and reasoning mechanisms integrated with deep learning-based systems to provide sound and explainable models for such systems. Neural-symbolic computing aims at integrating, as foreseen by Valiant, two most fundamental cognitive abilities: the ability to learn from the environment, and the ability to reason from what has been learned. Neural-symbolic computing has been an active topic of research for many years, reconciling the advantages of robust learning in neural networks and reasoning and interpretability of symbolic representation. In this paper, we survey recent accomplishments of neural-symbolic computing as a principled methodology for integrated machine learning and reasoning. We illustrate the effectiveness of the approach by outlining the main characteristics of the methodology: principled integration of neural learning with symbolic knowledge representation and reasoning allowing for the construction of explainable AI systems. The insights provided by neural-symbolic computing shed new light on the increasingly prominent need for interpretable and accountable AI systems

Indicadores de digestibilidade de dietas para ovinos contendo feno de ponta de cana-de-açúcar hidrolisado.

Made available in DSpace on 2017-12-18T23:24:49Z (GMT). No. of bitstreams: 1 RBSPA2017V18N1FENODEPONTADECANA.pdf: 190963 bytes, checksum: 9b647ac7ed3ea86ec0ade23af14eb5e5 (MD5) Previous issue date: 2017-12-18bitstream/item/169216/1/RBSPA-2017-V18-N1-FENO-DE-PONTA-DE-CANA.pd

Hydrolyzed sugarcane tip hay constitutes alternative forage in diets for finishing sheep.

The balance of nitrogen compounds was evaluated in finishing sheep fed diets containing hydrolyzed sugarcane tip hay. The experiment was carried out at the DZO/CCA/UFPI, in Teresina, PI, Brazil

Zika virus impairs the development of blood vessels in a mouse model of congenital infection

Zika virus (ZIKV) is associated with brain development abnormalities such as primary microcephaly, a severe reduction in brain growth. Here we demonstrated in vivo the impact of congenital ZIKV infection in blood vessel development, a crucial step in organogenesis. ZIKV was injected intravenously in the pregnant type 2 interferon (IFN)-deficient mouse at embryonic day (E) 12.5. The embryos were collected at E15.5 and postnatal day (P)2. Immunohistochemistry for cortical progenitors and neuronal markers at E15.5 showed the reduction of both populations as a result of ZIKV infection. Using confocal 3D imaging, we found that ZIKV infected brain sections displayed a reduction in the vasculature density and vessel branching compared to mocks at E15.5; altogether, cortical vessels presented a comparatively immature pattern in the infected tissue. These impaired vascular patterns were also apparent in the placenta and retina. Moreover, proteomic analysis has shown that angiogenesis proteins are deregulated in the infected brains compared to controls. At P2, the cortical size and brain weight were reduced in comparison to mock-infected animals. In sum, our results indicate that ZIKV impairs angiogenesis in addition to neurogenesis during development. The vasculature defects represent a limitation for general brain growth but also could regulate neurogenesis directly

Fast relational learning using bottom clause propositionalization with artificial neural networks

Relational learning can be described as the task of learning first-order logic rules from examples. It has enabled a number of new machine learning applications, e.g. graph mining and link analysis. Inductive Logic Programming (ILP) performs relational learning either directly by manipulating first-order rules or through propositionalization, which translates the relational task into an attribute-value learning task by representing subsets of relations as features. In this paper, we introduce a fast method and system for relational learning based on a novel propositionalization called Bottom Clause Propositionalization (BCP). Bottom clauses are boundaries in the hypothesis search space used by ILP systems Progol and Aleph. Bottom clauses carry semantic meaning and can be mapped directly onto numerical vectors, simplifying the feature extraction process. We have integrated BCP with a well-known neural-symbolic system, C-IL2P, to perform learning from numerical vectors. C-IL2P uses background knowledge in the form of propositional logic programs to build a neural network. The integrated system, which we call CILP++, handles first-order logic knowledge and is available for download from Sourceforge. We have evaluated CILP++ on seven ILP datasets, comparing results with Aleph and a well-known propositionalization method, RSD. The results show that CILP++ can achieve accuracy comparable to Aleph, while being generally faster, BCP achieved statistically significant improvement in accuracy in comparison with RSD when running with a neural network, but BCP and RSD perform similarly when running with C4.5. We have also extended CILP++ to include a statistical feature selection method, mRMR, with preliminary results indicating that a reduction of more than 90 % of features can be achieved with a small loss of accuracy

Speaker recognition with hybrid features from a deep belief network

Learning representation from audio data has shown advantages over the handcrafted features such as mel-frequency cepstral coefficients (MFCCs) in many audio applications. In most of the representation learning approaches, the connectionist systems have been used to learn and extract latent features from the fixed length data. In this paper, we propose an approach to combine the learned features and the MFCC features for speaker recognition task, which can be applied to audio scripts of different lengths. In particular, we study the use of features from different levels of deep belief network for quantizing the audio data into vectors of audio word counts. These vectors represent the audio scripts of different lengths that make them easier to train a classifier. We show in the experiment that the audio word count vectors generated from mixture of DBN features at different layers give better performance than the MFCC features. We also can achieve further improvement by combining the audio word count vector and the MFCC features

Efeito alelopático do extrato bruto de Brachiaria decumbens na germinação e no vigor de sementes e de plântulas de Brachiaria brizantha.

Objetivou-se identificar os possíveis efeitos alelopáticos produzidos pelo extrato bruto de um acesso da coleção de Brachiaria spp da Embrapa Gado de Corte, denominado Brachiaria decumbens BRA001996 na germinação, no vigor de sementes e no vigor de plântulas de três cultivares de B. brizantha (cvs. Marandu, BRS Piatã e Xaraés). As sementes das cultivares foram semeadas em papel germitest, colocadas em gerbox e incubadas em câmara climática com fotoperíodo controlado. Utilizaram-se quatro repetições de 100 sementes para os testes de germinação e vigor e 25 sementes para o teste de vigor de plântulas. O extrato bruto foi obtido das folhas da gramínea, por meio de técnica laboratorial utilizada para detecção e quantificação de avaliação de saponinas esteroidais. Foram avaliadas duas testemunhas: uma somente com água destilada e outra com água destilada e acrescida de 1% de DMSO e quatro concentrações: 1,85g/mL (10%); 3,7g/mL (20%); 5,55g/mL (30%) e 9,25 mg/mL (50%), totalizando seis tratamentos. Observou-se efeito ?dose-resposta? inibitório significativo (P<0,05) em todos as variáveis avaliadas, nas sementes das três cultivares estudadas. Sabendo-se que os compostos hormonais agem estimulando ou inibindo o metabolismo celular, sugere-se que os efeitos alelopáticos observados no presente trabalho possam estar relacionados ao efeito direto das saponinas esteroidais nas células das sementes e das plântulas das B. brizantha avaliadas. Conclui-se que o extrato bruto de Brachiaria decumbens BRA001996 reduz o vigor e a germinação das sementes, bem como o vigor das plântulas de Brachiaria brizantha, cultivares Xaraés, Piatã e Marandu.bitstream/item/68749/1/DOC188.pd

[C-11]PIB PET imaging can detect white and grey matter demyelination in a non-human primate model of progressive multiple sclerosis

Background: Multiple sclerosis (MS) is a demyelinating and inflammatory disease of the central nervous system. Its diagnosis is clinical, often confirmed by magnetic resonance imaging. This image modality, however, is not ideal for discrimination of demyelination in grey and white matter regions from inflammatory lesions. Positron Emission Tomography (PET), using specific radiopharmaceuticals, can be a tool to differentiate between these processes. The radiopharmaceutical [C-11]PIB is widely used for detection of beta-amyloid plaques, but has also been suggested for the analysis of myelin content due to its consistent uptake in white matter. The aim of this study was to evaluate [C-11]PIB PET imaging as a tool for detecting demyelinated regions in white and grey matter of non-human primate model of progressive MS. Methods: Experimental autoimmune encephalomyelitis (EAE) was induced in marmosets by injection of re-combinant human myelin oligodendrocyte glycoprotein (rhMOG) emulsified in either Incomplete Freund's Adjuvant (IFA) or Complete Freund's Adjuvant (CFA). [C-11]PIB PET images were acquired prior to immunization (baseline) and after symptoms were present (end of experiment). Brain tissue was isolated for histochemical analysis. Results: All rhMOG/IFA-treated and rhMOG/CFA-treated animals showed clinical signs of EAE. The rhMOG/CFA group presented a significant [C-11]PIB uptake reduction only in the left motor cortex (9%, P = 0.011). For the rhMOG/IFA group, significant decrease in [C-11]PIB uptake was observed in the whole brain (15%, P = 0.015), in the right hemisphere of body of corpus callosum (34%, P = 0.02), splenium of corpus callosum (38%, P = 0.004), hippocampus (19%, P = 0.036), optic tract (13%, P = 0.025), thalamus (14%, P = 0.041), Globus pallidus (23%, P = 0.017), head of caudate nucleus (25%, P = 0.045), tail of caudate nucleus (29%, P = 0.003), putamen (28%, P = 0.047) and left hemisphere of body of corpus callosum (14%, P = 0.037) and head of caudate nucleus (23%, P = 0.023). [C-11]PIB uptake significantly correlated with luxol fast blue histology (myelin marker), both in the rhMOG/IFA (r(2) = 0.32, P <0.0001) and the rhMOG/CFA group (r(2) = 0.46, P <0.0001). Conclusion: [C-11]PIB PET imaging is an efficient tool for detecting demyelination in grey and white matter, in a non-human primate model of progressive MS

Evaluation of rK39 rapid diagnostic tests for canine visceral leishmaniasis : longitudinal study and meta-analysis

Canine visceral leishmaniasis is a vector-borne disease caused by the intracellular parasite Leishmania infantum. It is an important veterinary disease, and dogs are also the main animal reservoir for human infection. The disease is widespread in the Mediterranean area, and parts of Asia and South and Central America, and is potentially fatal in both dogs and humans unless treated. Diagnosis of canine infections requires serological or molecular tests. Detection of infection in dogs is important prior to treatment, and in epidemiological studies and control programmes, and a sensitive and specific rapid diagnostic test would be very useful. Rapid diagnostic tests (RDTs) have been developed, but their diagnostic performance has been reported to be variable. We evaluated the sensitivity of a RDT based on serological detection of the rK39 antigen in a cohort of naturally infected Brazilian dogs. The sensitivity of the test to detect infection was relatively low, but increased with time since infection and the severity of infection. We then carried out a meta-analysis of published studies of rK39 RDTs, evaluating the sensitivity to detect disease and infection. The results suggest that rK39 RDTs may be useful in a veterinary clinical setting, but the sensitivity to detect infection is too low for operational control programmes

Specialist Peri-Operative Allergy Clinic Services in the UK 2016: Results from the Royal College of Anaesthetists Sixth National Audit Project (NAP6)

BACKGROUND: Guidelines for investigation of perioperative drug allergy exist, but the quality of services is unknown. Specialist perioperative anaphylaxis services were surveyed through the Royal College of Anaesthetists 6(th) National Audit Project. OBJECTIVES: We compare self-declared UK practice in specialist perioperative allergy services with national recommendations. METHODS: A SurveyMonkey(™) questionnaire was distributed to providers of allergy services in the UK. Responses were assessed for adherence to the best practice recommendations of the British Society for Allergy and Clinical Immunology, the Association of Anaesthetists of Great Britain and Ireland and the National Institute for Health and Care Excellence (NICE) Guidance on Drug Allergy - CG183. RESULTS: Over 1200 patients were evaluated in 44 centres annually. Variation in workload, waiting times, access, staffing and diagnostic approach was noted. Paediatric centres had the longest routine waiting times (most wait >13 weeks) in contrast to adult centres (most wait <12 weeks). Service leads are allergists/immunologists (91%) or anaesthetists (7%). Potentially important differences were seen in: testing repertoire [10/44 (23%) lacked BSACI compliant NMBA panels and 17/44 (39%) lacked a NAP6-defined extended panel; many failed to screen all cases for chlorhexidine 19/44 (43%) or latex 21/44 (48%)], staffing [only 26/44 (59%) had specialist nurses and 18/44 (41%) an anaesthetist], and provision of information [18/44 (41%) gave immediate information in clinic, and 5/44 (11%) on support groups]. Most centres were able to provide diagnostic challenges to antibiotics [40/44 (91%]) and local anaesthetics [41/44 (93%)]. CONCLUSIONS AND CLINICAL RELEVANCE: Diagnostic testing is not harmonised, with marked variability in the NMBA panels used to identify safe alternatives. Chlorhexidine and latex are not part of routine testing in many centres. Poor access to services and patient information provision require attention. Harmonisation of diagnostic approach is desirable, particularly with regard to a minimum NMBA panel for identification of safe alternatives. This article is protected by copyright. All rights reserved