Deception and self-awareness

This paper presents a study conducted for the Shades of Grey EPSRC research project (EP/H02302X/1), which aims to develop a suite of interventions for identifying terrorist activities. The study investigated the body movements demonstrated by participants while waiting to be interviewed, in one of two conditions: preparing to lie or preparing to tell the truth. The effect of self-awareness was also investigated, with half of the participants sitting in front of a full length mirror during the waiting period. The other half faced a blank wall. A significant interaction was found for the duration of hand/arm movements between the deception and self-awareness conditions (F=4.335, df=1;76, p<0.05). Without a mirror, participants expecting to lie spent less time moving their hands than those expecting to tell the truth; the opposite was seen in the presence of a mirror. This finding indicates a new research area worth further investigation

Negative aspects of counter-knowledge on absorptive capacity and human capital

People live and work in a world where they do not have complete knowledge and, as a result, they make use of rumours, beliefs and assumptions about relevant areas of concern. The term counter-knowledge has been used to refer to knowledge created from unverified sources. The purpose of this paper is to examine the relationship between counter-knowledge and human capital (HC) as well as investigating interactions between absorptive capacity (ACAP) and HC.The data of this research were taken from a research programme supported by the Spanish Ministry 
of Education (REF: ECO2011-28,641-C02-02) and the Mobility Project (REF: PRX14/00164)

Vehicle and Pedestrian Detection in Traffic Videos Using Convolutional Neural Networks

One of the major applications of computer vision is the analysis of the traffic scene on the road, and how pedestrian traffic affects traffic in general. Road sizes and traffic signals must constantly adapt. Counting and classifying vehicles and pedestrians at an intersection is an exhausting task, and despite the use of traffic control systems, human interaction is very necessary to perform such a task. The object of study of Deep Learning is to try to solve problems that require artificial intelligence. Artificial intelligence has been working in this field for years, with different approaches and algorithms. It has achieved an important emergence in the recognition of patterns in images and videos using these techniques, to the point of surpassing human capacity in some problems. An important factor in this development is the ability to process large volumes of information in applications, which has resulted in the devices used for this purpose, such as GPU’s and multi-core CPU’s, requiring a large amount of power to operate. For the development of the application of vehicle and pedestrian detection in traffic videos, YOLO V3 was used, which is a neural network model of the latest generation of real-time objects. Keywords: yoloV3, Deep Learning, Convolucional Network. Resumen Una de las mayores aplicaciones de la visión por computadora es el análisis de la escena de tráfico en la carretera, y cómo el tráfico de peatones afecta al tráfico en general. Los tamaños de las carreteras y las señales de tráfico deben adaptarse constantemente. Contar y clasificar vehículos y peatones en una intersección es una tarea agotadora y, a pesar del uso de sistemas de control de tráfico, la interacción humana es muy necesaria para realizar dicha tarea. El objeto de estudio de Deep Learning, es intentar resolver problemas que requieren inteligencia artificial. La inteligencia artificial ha trabajado en este campo durante años, con diferentes enfoques y algoritmos. Ha logrado un surgimiento importante en el reconocimiento de patrones en imágenes y videos usando estas técnicas, hasta el punto de superar la capacidad humana en algunos problemas. Un importante factor de este desarrollo es la capacidad de procesar grandes volúmenes de información en aplicaciones, lo que ha dado como resultado que los dispositivos utilizados para este propósito, como GPU’s y CPU’s multinúcleo, requieran una gran cantidad de energía para operar. Para el desarrollo de la aplicación de Detección de vehículos y peatones en videos de tráfico, fue utilizado YOLO V3, que es un modelo de red neuronal de la última generación de objetos en tiempo real. Palabras Clave: yoloV3, Aprendizaje profundo, Red convoluciona

Organizational unlearning context fostering learning for customer capital through time: lessons from smes in the telecommunications industry

In situations where organizations and their members face changing environments it is necessary that old knowledge represented in processes and routines be challenged prior to the addition of new knowledge. It could be claimed that for learning to occur on an organizational level it must be possible for unlearning to take place. However, there have been few, if any, studies providing direct empirical evidence for this relationship. In the analysis presented in this paper we explicitly include time as a variable in order to model a situation where unlearning at time (t0) in order to learn more efficiently at a moment after occurs prior to time (t1). In addition, we also examine the relationship between organizational learning and customer capital. These relationships are examined through an empirical investigation of 107 Spanish small and medium sized enterprises (SMEs) from the Telecommunications industry. The results indicate that the effect of the unlearning at a moment (t0) on customer capital at a moment (t1) is depends on whether the learning taking place at (t1) can be characterized as either exploration or exploitation

On the probable composition of ‘Jamaican stone’ aphrodisiac

A dangerous aphrodisiac, commonly known as ‘Jamaican stone’, banned by the U.S. Food and Drug Administration, has been studied by vibrational spectroscopy in order to solve the controversy on its composition. The results of the ATR-FTIR analysis revealed the presence of the a-pyrone ring, which is characteristic of bufadienolides from toad venom and bulbs of squill (Drimia maritima (L.) Stearn). This conclusion was reached after a comparative study with the spectra for phytochemicals derived from gambir and cat''s claw, two Uncaria species also preconized as aphrodisiacs and deemed as possible constituents of the ‘stone’. Owing to their physiologic similarities to digoxin, bufadienolides have been shown to produce a toxic profile similar to that of digoxin, although the lack one of the side chains found on digoxin should allow the use of hemodialysis to treat ‘Jamaican stone’ overdose

Vibrational analysis and thermal behavior of salvia hispanica, nigella sativa and papaver somniferum seeds

Introduction: Salvia hispanica L., Nigella sativa L. and Papaver somniferum L. are involved in opiate-dependent behavior. It is known that the seeds of these three herbs contain high amounts of antioxidants, which are helpful in disease prevention, but further research is needed on some of their other phytochemical components (terpene alkaloids, benzoquinones and others), which are claimed to affect human opioid receptors. Methods: Seeds from the three afore mentioned plants have been studied by ATR-FTIR vibrational spectroscopy and thermo analytical techniques (TG/DTG, DTA and DSC). Results: The infrared spectrum has confirmed the presence of the ester carbonyl of terpenoid alkaloids (such as nigellamine) and the fully conjugated cyclic dione structure of quinones (e.g., thymoquinone). As regards the thermal stability of these seeds, small differences have been observed in their thermal profiles (endothermic effects at around 333C for chia, 268C for black cumin and 319C for poppy seeds), which can be ascribed to their different content in carbohydrates. Conclusions: The functional groups of the main active constituents and the thermal behavior of these three seeds have been elucidated

Valorization of Cistus ladanifer and Erica arborea shrubs for fuel: Wood and bark thermal characterization

As a form of upgraded biomass characterized by its high energy density, low production costs, and low process energy requirements, wood pellets are an environmentally friendly fuel allowing for carbon neutral heating with high energy efficiency. In this work, the suitability of a valorization of the woods from the two most representative shrub species from the Iberian Peninsula (namely Cistus ladanifer and Erica arborea) for heating has been assessed. Whereas Erica arborea met the requirements of ISO 17225-2:2014 for ENplus-B class (the calorific content for both wood and bark was high and not significantly different, and the ash content was permissible for specimens with branch diameter =2, 8 cm), Cistus ladanifer was in the limit of the normative and only met the requirements in terms of acceptable ash percentage (1, 9%) and heating value (19 kJ·g-1) for old specimens with branch diameters &gt; 3, 4 cm. Consequently, while the harvest of E. arborea for its use as fuel does not need to be selective, that of C. ladanifer should be limited to the most robust specimens and foliage should be avoided