A generative adversarial network for single and multi-hop distributional knowledge base completion

Knowledge bases (KBs) inherently lack reasoning ability, limiting their effectiveness for tasks such as question-answering and query expansion. Machine-learning is hence commonly employed for representation learning in order to learn semantic features useful for generalization. Most existing methods utilize discriminative models that require both positive and negative samples to learn a decision boundary. KBs, by contrast, contain only positive samples, necessitating that negative samples are generated by replacing the head/tail of predicates with randomly-chosen entities. They are thus frequently easily discriminable from positive samples, which can prevent learning of sufficiently robust classifiers. Generative models, however, do not require negative samples to learn the distribution of positive samples; stimulated by recent developments in Generative Adversarial Networks (GANs), we propose a novel framework, Knowledge Completion GANs (KCGANs), for competitively training generative link prediction models against discriminative belief prediction models. KCGAN thus invokes a game between generator-network G and discriminator-networkD in which G aims to understand underlying KB structure by learning to perform link prediction while D tries to gain knowledge about the KB by learning predicate/triplet classification. Two key challenges are addressed: 1) Classical GAN architectures’ inability to easily generate samples over discrete entities; 2) the inefficiency of softmax for learning distributions over large sets of entities. As a step toward full first-order logical reasoning we further extend KCGAN to learn multi-hop logical entailment relations between entities by enabling G to compose a multi-hop relational path between entities and D to discriminate between real and fake paths. KCGAN is tested on benchmarks WordNet and FreeBase datasets and evaluated on link prediction and belief prediction tasks using MRR and HIT@10, achieving best-in-class performance

Coarsening of "clouds" and dynamic scaling in a far-from-equilibrium model system

A two-dimensional lattice gas of two species, driven in opposite directions by an external force, undergoes a jamming transition if the filling fraction is sufficiently high. Using Monte Carlo simulations, we investigate the growth of these jams ("clouds"), as the system approaches a non-equilibrium steady state from a disordered initial state. We monitor the dynamic structure factor $S(k_x,k_y;t)$ and find that the $k_x=0$ component exhibits dynamic scaling, of the form $S(0,k_y;t)=t^\beta \tilde{S}(k_yt^\alpha)$. Over a significant range of times, we observe excellent data collapse with $\alpha=1/2$ and $\beta=1$. The effects of varying filling fraction and driving force are discussed

A generative adversarial strategy for modeling relation paths in knowledge base representation learning

Enabling neural networks to perform multi-hop (mh) reasoning over knowledge bases (KBs) is vital for tasks such as question-answering and query expansion. Typically, recurrent neural networks (RNNs) trained with explicit objectives are used to model mh relation paths (mh-RPs). In this work, we hypothesize that explicit objectives are not the most effective strategy effective for learning mh-RNN reasoning models, proposing instead a generative adversarial network (GAN) based approach. The proposed model – mh Relation GAN (mh-RGAN) – consists of two networks; a generator $G$, and discriminator $D$. $G$ is tasked with composing a mh-RP and $D$ with discriminating between real and fake paths. During training, $G$ and $D$ contest each other adversarially as follows: $G$ attempts to fool $D$ by composing an indistinguishably invalid mh-RP given a head entity and a relation, while $D$ attempts to discriminate between valid and invalid reasoning chains until convergence. The resulting model is tested on benchmarks WordNet and FreeBase datasets and evaluated on the link prediction task using MRR and HIT@ 10, achieving best-in-class performance in all cases

The Synthesis and Characterization of New, Robust Titanium (IV) Scorpionate Complexes

Titanium complexes possessing sterically encumbered ligands have allowed for the preparation of reactive moieties (imido, alkylidene and alkylidyne species) relevant to reactions such as olefin polymerization and alkyne hydroamination. For this reason, we have targeted robust scorpionate ancillary ligands to support reactive titanium centers. Thus, a series of titanium complexes were synthesized using an achiral oxazoline-based scorpionate ligand, tris(4,4-dimethyl-2-oxazolinyl)phenyl borate [To^M^]^-^ as well as the related chiral ligand, tris(4-isopropyl-2-oxazolinyl)phenyl borate [To^P^]^-^. The complex [Ti(κ^3^- To^M^)Cl~3~] was prepared in moderate yield (43%) by the rapid (<1 min at room temperature) reaction of Li[To^M^] and TiCl~4~ in methylene chloride; this new compound was characterized by ^1^H NMR spectroscopy as the expected C~3v~-symmetric species. One route to Ti (IV) alkyls involves salt metathesis; accordingly, syntheses of [To^M^]Ti alkyl complexes by interaction of [Ti(κ^3^-To^M^)Cl~3~] and one or three equivalents of alkylating agents, such as benzyl potassium (KCH~2~C~6~H~5~), trimethylsilylmethyl
lithium (LiCH~2~Si(CH~3~) ~3~), or neopentyl lithium (LiCH~2~C(CH~3~)~3~) are currently under investigation. The complexes [Ti(=NBut) (κ~3~-To^M^)(Cl)(Bu^t^py)] (Bu^t^py=4 tert-butylpyridine) and [Ti(=NBu^t^) (κ~3~-To^P^)(Cl)(Bu^t^py)] were synthesized by reaction of the known Ti imido [Ti(=NBu^t^)(Cl)~2~(Bu^t^py)~2~] with Li[To^M^] or Li[To^P^], respectively, by stirring overnight in methylene chloride at ambient temperature. The complexes were identified using ^1^H NMR spectroscopy, ^1^H-^13^C HMQC and ^1^H-^15^N HMBC correlation experiments

The In vitro Effectiveness of Oxalate Based Desensitizing Products on Tubular Occlusion

Introduction: Dentine hypersensitivity (DH) is one of the most common clinically encountered conditions globally, affecting up to 74%. It has been described as a short, sharp pain resulting from changes in the fluid flow of exposed dentinal tubules, in response to physical and chemical stimuli. Objective: To compare the effectiveness of oxalate containing desensitizing products in reducing both dentine permeability and tubular occlusion vs. a control product using a recognized in vitro model. Methods: Three oxalate containing products were tested (Listerine® Advanced Defence Sensitive [LADS] mouth rinse, a 3% oxalate solution and an oxalate containing herbal toothpaste), vs. an artificial saliva control. The permeability of the acid-etched dentine discs was measured by hydraulic conductance (Lp). Dentine discs were examined using scanning electron microscopy and energy dispersive X-ray spectroscopy. After establishing the baseline permeability of the acid-etched dentine discs, discs (n=4) were randomly treated with the desensitizing products together with the addition of artificial saliva for 2 mins, followed by rinsing with distilled water (60 s). Permeability was measured at 30 s intervals for a total of 150 s. The occluded discs were acid challenged to assess tubular occlusion stability following the application of both the test and control products. Results: The oxalate containing desensitizing products in combination with artificial saliva significantly occluded the dentinal tubules by up to 65%, in comparison to the artificial saliva control that occluded ≤21% of the dentinal tubules. The occlusion associated with the oxalate containing desensitizing agents was substantially more stable in resisting an acid challenge compared to the control as determined by hydraulic conductance. Furthermore, the SEM images of the oxalate containing desensitising agents and control were consistent with the hydraulic conductance data. Of interest was that the oxalate containing herbal toothpaste deposited more precipitation on the surface than inside the tubules. The EDX analysis confirmed the presence of oxalates, calcium, and other ingredients of toothpaste. The results from the present study are in broad agreement with those of a previous study in that an oxalate containing mouth rinse provided a more stable tubular occlusion which was more resistant to an acid challenge compared to the other test products. Conclusion: Oxalate containing desensitizing agents were significantly more effective in occluding the dentinal tubules vs. an artificial saliva control. These results are of clinical significance as they demonstrate that oxalate containing desensitizing agents provide both significant and stable tubular occlusion of the open dentinal tubules following an acidic challenge

Comment on `Renormalization-Group Calculation of the Dependence on Gravity of the Surface Tension and Bending Rigidity of a Fluid Interface'

It is shown that the interface model introduced in Phys. Rev. Lett. 86, 2369 (2001) violates fundamental symmetry requirements for vanishing gravitational acceleration $g$, so that its results cannot be applied to critical properties of interfaces for $g\to 0$.Comment: A Comment on a recent Letter by J.G. Segovia-L\'opez and V. Romero-Roch\'{\i}n, Phys. Rev. Lett.86, 2369 (2001). Latex file, 1 page (revtex

Jumlah Uang Saku Dan Kebiasaan Melewatkan Sarapan Berhubungan Dengan Status Gizi Lebih Anak Sekolah Dasar

The prevalence of overnutrition in Indonesia is increasing from year to year. Overnutrition occurs because of an imbalance between consumed and expended energy. Overnutrition needs a serious attention because it deals with a variety of health problem complications in adult, such as diabetes and heart disease. This research aims to analyze the association between the amount of pocket money and breakfast habit with overnutrition status in elementary school children. Analytical observational research with cross sectional design was conducted in SDN Ploso I-172 Tambaksari Surabaya. The sample size was 52, which was taken by using simple random sampling technique in 4th and 5th grade students. Association among variables were analyzed using Chi-Square test. The result showed that 32.7% of respondents skip breakfast. The mean of respondent's pocket money was IDR 5.894,23 ± 3.215,06. Majority of respondents were obese (34.6%) and overweight (28.8%). Chi-Square test showed there was an association between the amount of pocket money (p=0.000) and breakfast habits (p=0.005) with overnutrition status. It can be concluded that the amount of pocket money and breakfast skipping habit contribute to overnutrition status in elementary school children. Parents are responsible for providing foods with adequate nutrition for children, habituate children to have breakfast at home, and provide pocket money to children with amount less than IDR 5.894,23 ± 3.215,06

Multi-view convolutional recurrent neural networks for lung cancer nodule identification

Screening via low-dose Computer Tomography (CT) has been shown to reduce lung cancer mortality rates by at least 20%. However, the assessment of large numbers of CT scans by radiologists is cost intensive, and potentially produces varying and inconsistent results for differing radiologists (and also for temporally-separated assessments by the same radiologist). To overcome these challenges, computer aided diagnosis systems based on deep learning methods have proved an effective in automatic detection and classification of lung cancer. Latterly, interest has focused on the full utilization of the 3D information in CT scans using 3D-CNNs and related approaches. However, such approaches do not intrinsically correlate size and shape information between slices. In this work, an innovative approach to Multi-view Convolutional Recurrent Neural Networks (MV-CRecNet) is proposed that exploits shape, size and cross-slice variations while learning to identify lung cancer nodules from CT scans. The multiple-views that are passed to the model ensure better generalization and the learning of robust features. We evaluate the proposed MV-CRecNet model on the reference Lung Image Database Consortium and Image Database Resource Initiative and Early Lung Cancer Action Program datasets; six evaluation metrics are applied to eleven comparison models for testing. Results demonstrate that proposed methodology outperforms all of the models against all of the evaluation metrics

Solving dielectric and plasmonic waveguide dispersion relations with a pocket calculator

We present a robust iterative technique for solving complex transcendental dispersion equations routinely encountered in integrated optics. Our method especially befits the multilayer dielectric and plasmonic waveguides forming the basis structures for a host of contemporary nanophotonic devices. The solution algorithm ports seamlessly from the real to the complex domain--i.e., no extra complexity results when dealing with leaky structures or those with material/metal loss. Unlike several existing numerical approaches, our algorithm exhibits markedly-reduced sensitivity to the initial guess and allows for straightforward implementation on a pocket calculator.Comment: 18 pages, 11 Figures, 5 Tables, added references, Submitted to Optics Expres