Leverage instability and persistence: Evidence from the United States and Europe

We find that leverage behavior both in level and time-series variation is very similar between the United States and Europe throughout the 1990-2013 period. Leverage regimes are simultaneously unstable and persistent for both regions. We define instability as the extent to which firms largely deviate from their long-term leverage mean, while persistence as the extent to which today’s leverage influences its future levels. We then show that this simultaneous evidence imply a mean-reversion behavior of leverage and discuss some of its implications for future research on this field.

Fouling of a drinking water system in relation to hydraulic circumstances and customer complaints

In a “perfect” drinking water system, the water quality for the consumers should be the same as the quality of the water leaving the treatment plant. However, some variability along the system can lead to a decrease in water quality (such as discolouration) which is usually reflected in the number of the customer complaints. This change may be related to the amount of sediment in the distribution network, leading to an increase in turbidity at the water supply. Since there is no such thing as a perfect drinking water system, the behaviour of particles in a drinking water network needs a suitable approach in order to understand how it works. Moreover, the combination of measurements, such as turbidity patterns and the Resuspension Potential Method (RPM) aid in the prevention of discoloured water complaints and intervention in the treatment upgrade or the network cleaning. Besides sediments there is also bacterial regrowth in the network, which is related to the water quality and distribution network characteristics. In a theoretical drinking water system higher velocities, temperature and shorter residences times lead to wider bacterial growth. In this study we observe velocity and residence steady-states and bacterial does not seem to be related to either. It can be concluded that adequate measurements of RPM, customer complaints and bacterial concentrations allow a wider knowledge on particle behaviour in drinking water systems.

Knowledge management framework based on brain models and human physiology

The life of humans and most living beings depend on sensation and perception for the best assessment of the surrounding world. Sensorial organs acquire a variety of stimuli that are interpreted and integrated in our brain for immediate use or stored in memory for later recall. Among the reasoning aspects, a person has to decide what to do with available information. Emotions are classifiers of collected information, assigning a personal meaning to objects, events and individuals, making part of our own identity. Emotions play a decisive role in cognitive processes as reasoning, decision and memory by assigning relevance to collected information. The access to pervasive computing devices, empowered by the ability to sense and perceive the world, provides new forms of acquiring and integrating information. But prior to data assessment on its usefulness, systems must capture and ensure that data is properly managed for diverse possible goals. Portable and wearable devices are now able to gather and store information, from the environment and from our body, using cloud based services and Internet connections. Systems limitations in handling sensorial data, compared with our sensorial capabilities constitute an identified problem. Another problem is the lack of interoperability between humans and devices, as they do not properly understand human’s emotional states and human needs. Addressing those problems is a motivation for the present research work. The mission hereby assumed is to include sensorial and physiological data into a Framework that will be able to manage collected data towards human cognitive functions, supported by a new data model. By learning from selected human functional and behavioural models and reasoning over collected data, the Framework aims at providing evaluation on a person’s emotional state, for empowering human centric applications, along with the capability of storing episodic information on a person’s life with physiologic indicators on emotional states to be used by new generation applications.