API Requirements for Dynamic Graph Prediction

Given a large-scale time-evolving multi-modal and multi-relational complex network (a.k.a., a large-scale dynamic semantic graph), we want to implement algorithms that discover patterns of activities on the graph and learn predictive models of those discovered patterns. This document outlines the application programming interface (API) requirements for fast prototyping of feature extraction, learning, and prediction algorithms on large dynamic semantic graphs. Since our algorithms must operate on large-scale dynamic semantic graphs, we have chosen to use the graph API developed in the CASC Complex Networks Project. This API is supported on the back end by a semantic graph database (developed by Scott Kohn and his team). The advantages of using this API are (i) we have full-control of its development and (ii) the current API meets almost all of the requirements outlined in this document

A Doorway Detection and Direction (3Ds) System for Social Robots via a Monocular Camera

In this paper, we propose a novel algorithm to detect a door and its orientation in indoor settings from the view of a social robot equipped with only a monocular camera. The challenge is to achieve this goal with only a 2D image from a monocular camera. The proposed system is designed through the integration of several modules, each of which serves a special purpose. The detection of the door is addressed by training a convolutional neural network (CNN) model on a new dataset for Social Robot Indoor Navigation (SRIN). The direction of the door (from the robot’s observation) is achieved by three other modules: Depth module, Pixel-Selection module, and Pixel2Angle module, respectively. We include simulation results and real-time experiments to demonstrate the performance of the algorithm. The outcome of this study could be beneficial in any robotic navigation system for indoor environments

Insider trading, regulation and the components of the Bid-Ask Spread

Insiders pose a risk to providers of liquidity, who require compensation for this and consequentially widen spreads. In this paper we investigate the relationship between insider trading regulation and the cost of trading by decomposing the components of the spread before and after the enactment of strict new laws. We find a significant decrease in information asymmetry, which is mainly observed in illiquid and high prechange information asymmetry companies. Results are robust to model specification. We also see a decrease in the contribution of information asymmetry to price volatility. Overall, our results may have implications for markets with similar characteristics

Do criminal sanctions deter insider trading?

Many developed markets have taken what appears to be a tough stance on illegal insider trading through the use of criminal sanctions. Although criminal sanctions represent a much greater penalty than civil sanctions, the higher burden of proof required makes their enforceability weaker. This trade-off between severity and enforceability makes the impact of criminal sanctions ambiguous. In this paper, we empirically examine this issue by studying the deterrence of insider trading following the introduction of criminal sanctions in a developed market. Significant changes in sanction regimes are rare, especially when criminal sanctions are introduced without other changes. In February 2008, New Zealand introduced criminal sanctions for insider trading. This change of law offers a unique setting in which to examine the deterrence effect of criminalization. Using measures for the cost of trading, degree of information asymmetry, and probability of informed trading, we find that the enactment of this law led to a worsening in these measures. These findings suggest that the weaker enforceability of criminalization outweighs the associated increased severity of the penalties

Histochemical study of the oesophagus in the chukar partridge (Alectoris chukar) embryo

Study of the histogenesis of different organs is a useful laboratory method which helps us achieve accurate basic information about organ development during the embryonic period. It also reveals histological differences of each organ in different species. This research was carried out to study the histogenesis of the oesophagus of chukar partridge. For this purpose, the embryonated eggs were placed in the incubator and the embryos were collected between the 5th to 24th days of incubation period. The specimens were fixed in Bouin’s solution, and routine histotechnique processes were performed. The slides were finally stained with haematoxylin-eosin, Periodic Acid Schiff, Alcian Blue and Masson Trichrome, and the developmental changes of the oesophagus during the embryonic period were studied by light microscope. The four layers of oesophagus, including, the mucosa, submucosa, tunica muscularis and advantitia/serosa, both in cervical and thoracic oesophagus, were studied. During days 5 to 24 of incubation, developmental events in the oesophagus such as changes in the oesophageal epithelium, formation of muscularis mucosae and tunica muscularis, development of the mucous glands and the type of their secretion, were observed. Finally the results were compared with those of other studied avian species and the similarities and differences were discussed

A Brain-Inspired Multi-Modal Perceptual System for Social Robots: An Experimental Realization

We propose a multi-modal perceptual system that is inspired by the inner working of the human brain; in particular, the hierarchical structure of the sensory cortex and the spatial-temporal binding criteria. The system is context independent and can be applied to many on-going problems in social robotics, including but not limited to person recognition, emotion recognition, and multi-modal robot doctor to name a few. The system encapsulates the parallel distributed processing of real-world stimuli through different sensor modalities and encoding them into features vectors which in turn are processed via a number of dedicated processing units (DPUs) through hierarchical paths. DPUs are algorithmic realizations of the cell assemblies in neuroscience. A plausible and realistic perceptual system is presented via the integration of the outputs from these units by spiking neural networks. We will also discuss other components of the system including top-down influences and the integration of information through temporal binding with fading memory and suggest two alternatives to realize these criteria. Finally, we will demonstrate the implementation of this architecture on a hardware platform as a social robot and report experimental studies on the system

Veronica persica Poir. extract - antibacterial, antifungal and scolicidal activities, and inhibitory potential on acetylcholinesterase, tyrosinase, lipoxygenase and xanthine oxidase

Veronica persica (Persian speedwell) is a flowering plant local to Eurasia. In this study, several analyses were done to discover the antimicrobial and scolicidal activities and acetyl cholinesterase (AChE), tyrosinase (TYR), lipoxygenase (LOX), and xanthine oxidase (XO) inhibitory activities of V. persica extract. The results presented that B. subtilis was the most susceptible to the extract (MIC = 40.3 \u3bcg/mL), while P. aeruginosa was the most resistant strain (MIC = 250.9 \u3bcg/mL) among all bacteria evaluated. The extracts demonstrated significant activity versus E. granulosus (P < 0.5) with dose-dependent inhibitions of the protoscolices. The analyzed plant extract exhibited a high AChE and TYR inhibitory activity 55.3% and 52.7% (at the highest utilized dose - 3 mg/mL), respectively. The extract also showed high anti-inflammatory activities in analyses tested. Our research proposed that extract of this plant could be promising to the human health, markedly in the infectious, neurodegenerative and inflammatory disorders

Susceptibility of Leishmania major to Veronica persica Poir. extracts - In vitro and in vivo assays

Leishmania major is an intracellular parasite generally responsible for cutaneous leishmaniasis (CL), one of the most encountered skin diseases especially in Pakistan, Iran, Iraq, and Saudi Arabia. Current treatment options are not ideal, due to unwanted side effects and increasing resistance and availability is often limited in developing countries. Medicinal plants continue to attract attention because of their beneficial effects in the prevention or/and accelerating the healing process of various diseases. In this study, in vitro and in vivo susceptibility of L. major to Veronica persica Poir. extract, a medicinal plant with many applications, has been evaluated. Antileishmanial activity of plant extract was investigated both on cultured L. major promastigotes and in mice challenged with L. major. Animals were divided into three groups including control (without any treatment), test (treated with plant extract) and glucantime (the reference drug) treated groups. After treatments, skin lesion sizes and body weights of animals were checked during 4 weeks. The potential of the plant extract in decreasing the number of parasites in spleen cells of animals as well as inducing the nitric oxide (NO) production by macrophage cells was also investigated. In vitro tests showed that the plant extract was able to reduce the survival time of promastigotes in a concentration-dependent manner. In vivo experiments also revealed a significant influence of V. persica extracts on accelerating the healing process as well as reducing the overall disease burden in animal model by inducing NO production in macrophage cells. Our findings indicated the promising potential of V. persica extract as an ideal candidate in the treatment of CL caused by L. major