Model and visualise the relationship between energy consumption and temperature distribution in cold rooms

In the area of food and pharmacy cold storage, temperature distribution is considered as a key factor. Inappropriate distribution of temperature during the cooling process in cold rooms will cause the deterioration of the quality of products and therefore shorten their life-span. In practice, in order to maintain the distribution of temperature at an appropriate level, large amount of electrical energy has to be consumed to cool down the volume of space, based on the reading of a single temperature sensor placed in every cold room. However, it is not clear and visible that what is the change of energy consumption and temperature distribution over time. It lacks of effective tools to visualise such a phenomenon. In this poster, we initially present a solution which combines a visualisation tool with a Computational Fluid Dynamics (CFD) model together to enable users to explore such phenomenon.

Optimised crystal morphologies for active pharmaceutical ingredients and related studies

The majority of active pharmaceutical ingredients (APIs) are crystalline solids in their pure forms. Crystalline solids have definable morphologies, i.e. shape and size. Crystal morphology is determined by both the internal structure of the crystals and external factors during growth from solution. The morphology of a crystal batch can affect key processes during manufacturing. Companies generally accept whatever morphology the manufacturing process provides and deal with any subsequent problems by costly trouble‒shooting. Rational design of optimised morphologies for crystalline pharmaceutical solids would be a very significant technical and commercial advance. Chapter one introduces the concept of crystal nucleation and growth. The phenomenon of polymorphism alongside the causes and impact is discussed. A summary of the scope of instrumentation used in the investigation of crystal polymorphism and morphology, including crystal size distribution (CSD), is also included. Chapter two examines the research carried out during an exploration of the optimum crystallisation parameters of phenacetin. Following a morphological study, the impact this induces on particle density and flow properties is examined. The impact of impurities on the crystallisation properties of phenacetin is investigated. Significantly, the location of impurities within individual crystals is also studied. The third chapter describes an industrial collaboration looking at the resolution and polymorphic study of trometamol and lysine salts of ketoprofen and 2‒phenylpropionic acid (2‒PPA). Chapter four incorporates a solid state study on three separate compounds: 2‒chloro‒4‒nitroaniline, 4‒hydroxy‒N‒phenylbenzenesulfonamide and N‒acetyl‒D‒glucosamine‒6‒O‒sulfate. 2‒Chloro‒4‒nitroaniline and 4‒hydroxy‒N‒phenylbenzenesulfonamide both produced interesting, extreme morphologies which warranted further investigation as part of a collaborative study. Following a summarisation of results in chapter five, chapter six contains the full experimental details, incorporating spectral and other analytical data for all compounds synthesised during the course of the research.

ALD: adaptive layer distribution for scalable video

Recent years have witnessed a rapid growth in the demand for streaming video over the Internet and mobile networks, exposes challenges in coping with heterogeneous devices and varying network throughput. Adaptive schemes, such as scalable video coding, are an attractive solution but fare badly in the presence of packet losses. Techniques that use description-based streaming models, such as multiple description coding (MDC), are more suitable for lossy networks, and can mitigate the effects of packet loss by increasing the error resilience of the encoded stream, but with an increased transmission byte cost. In this paper, we present our adaptive scalable streaming technique adaptive layer distribution (ALD). ALD is a novel scalable media delivery technique that optimises the tradeoff between streaming bandwidth and error resiliency. ALD is based on the principle of layer distribution, in which the critical stream data are spread amongst all packets, thus lessening the impact on quality due to network losses. Additionally, ALD provides a parameterised mechanism for dynamic adaptation of the resiliency of the scalable video. The Subjective testing results illustrate that our techniques and models were able to provide levels of consistent high-quality viewing, with lower transmission cost, relative to MDC, irrespective of clip type. This highlights the benefits of selective packetisation in addition to intuitive encoding and transmission.

ALD: adaptive layer distribution for scalable video

Bandwidth constriction and datagram loss are prominent issues that affect the perceived quality of streaming video over lossy networks, such as wireless. The use of layered video coding seems attractive as a means to alleviate these issues, but its adoption has been held back in large part by the inherent priority assigned to the critical lower layers and the consequences for quality that result from their loss. The proposed use of forward error correction (FEC) as a solution only further burdens the bandwidth availability and can negate the perceived benefits of increased stream quality. In this paper, we propose Adaptive Layer Distribution (ALD) as a novel scalable media delivery technique that optimises the tradeoff between the streaming bandwidth and error resiliency. ALD is based on the principle of layer distribution, in which the critical stream data is spread amongst all datagrams thus lessening the impact on quality due to network losses. Additionally, ALD provides a parameterised mechanism for dynamic adaptation of the scalable video, while providing increased resilience to the highest quality layers. Our experimental results show that ALD improves the perceived quality and also reduces the bandwidth demand by up to 36% in comparison to the well-known Multiple Description Coding (MDC) technique.

On the multiple ecological roles of water in river networks

The distribution and movement of water can influence the state and dynamics of terrestrial and aquatic ecosystems through a diversity of mechanisms. These mechanisms can be organized into three general categories wherein water acts as (1) a resource or habitat for biota, (2) a vector for connectivity and exchange of energy, materials, and organisms, and (3) as an agent of geomorphic change and disturbance. These latter two roles are highlighted in current models, which emphasize hydrologic connectivity and geomorphic change as determinants of the spatial and temporal distributions of species and processes in river systems. Water availability, on the other hand, has received less attention as a driver of ecological pattern, despite the prevalence of intermittent streams, and strong potential for environmental change to alter the spatial extent of drying in many regions. Here we summarize long-term research from a Sonoran Desert watershed to illustrate how spatial patterns of ecosystem structure and functioning reflect shifts in the relative importance of different 'roles of water' across scales of drainage size. These roles are distributed and interact hierarchically in the landscape, and for the bulk of the drainage network it is the duration of water availability that represents the primary determinant of ecological processes. Only for the largest catchments, with the most permanent flow regimes, do flood-associated disturbances and hydrologic exchange emerge as important drivers of local dynamics. While desert basins represent an extreme case, the diversity of mechanisms by which the availability and flow of water influence ecosystem structure and functioning are general. Predicting how river ecosystems may respond to future environmental pressures will require clear understanding of how changes in the spatial extent and relative overlap of these different roles of water shape ecological patterns. © 2013 Sponseller et al.

Dynamic evolution in information sharing networks

This study examines the roll-out of a collaborative information repository or 'knowledge-base' in a medium-sized UK professional services firm over a six year period. Data from usage logs provides the basis for analysis of the dynamic evolution of social networks around the depository during this time. The adoption pattern follows an 's-curve' and usage exhibits something of a power law distribution, both attributable to network effects and network opposition is associated with organisational performance on a number of indicators. But periodicity in usage is evident and the usage distribution displays an exponential cut-off. Fourier analysis provides some evidence of mathematical complexity in the periodicity. Some implications of complex patterns in social network data for research and management are discussed.

Evaluating the SEVIRI Fire Thermal Anomaly Detection Algorithm across the Central African Republic Using the MODIS Active Fire Product

Satellite-based remote sensing of active fires is the only practical way to consistently and continuously monitor diurnal fluctuations in biomass burning from regional, to continental, to global scales. Failure to understand, quantify, and communicate the performance of an active fire detection algorithm, however, can lead to improper interpretations of the spatiotemporal distribution of biomass burning, and flawed estimates of fuel consumption and trace gas and aerosol emissions. This work evaluates the performance of the Spinning Enhanced Visible and Infrared Imager (SEVIRI) Fire Thermal Anomaly (FTA) detection algorithm using seven months of active fire pixels detected by the Moderate Resolution Imaging Spectroradiometer (MODIS) across the Central African Republic (CAR). Results indicate that the omission rate of the SEVIRI FTA detection algorithm relative to MODIS varies spatially across the CAR, ranging from 25% in the south to 74% in the east. In the absence of confounding artifacts such as sunglint, uncertainties in the background thermal characterization, and cloud cover, the regional variation in SEVIRI's omission rate can be attributed to a coupling between SEVIRI's low spatial resolution detection bias (i.e., the inability to detect fires below a certain size and intensity) and a strong geographic gradient in active fire characteristics across the CAR. SEVIRI's commission rate relative to MODIS increases from 9% when evaluated near MODIS nadir to 53% near the MODIS scene edges, indicating that SEVIRI errors of commission at the MODIS scene edges may not be false alarms but rather true fires that MODIS failed to detect as a result of larger pixel sizes at extreme MODIS scan angles. Results from this work are expected to facilitate (i) future improvements to the SEVIRI FTA detection algorithm; (ii) the assimilation of the SEVIRI and MODIS active fire products; and (iii) the potential inclusion of SEVIRI into a network of geostationary sensors designed to achieve global diurnal active fire monitoring.

Activation of Akt/PKB, increased phosphorylation of Akt substrates and loss and altered distribution of Akt and PTEN are features of Alzheimer's disease pathology

Studies suggest that activation of phosphoinositide 3-kinase-Akt may protect against neuronal cell death in Alzheimer's disease (AD). Here, however, we provide evidence of increased Akt activation, and hyperphosphorylation of critical Akt substrates in AD brain, which link to AD pathogenesis, suggesting that treatments aiming to activate the pathway in AD need to be considered carefully. A different distribution of Akt and phospho-Akt was detected in AD temporal cortex neurons compared with control neurons, with increased levels of active phosphorylated-Akt in particulate fractions, and significant decreases in Akt levels in AD cytosolic fractions, causing increased activation of Akt (phosphorylated-Akt/total Akt ratio) in AD. In concordance, significant increases in the levels of phosphorylation of total Akt substrates, including: GSK3ßSer9, tauSer214, mTORSer2448, and decreased levels of the Akt target, p27kip1, were found in AD temporal cortex compared with controls. A significant loss and altered distribution of the major negative regulator of Akt, PTEN (phosphatase and tensin homologue deleted on chromosome 10), was also detected in AD neurons. Loss of phosphorylated-Akt and PTEN-containing neurons were found in hippocampal CA1 at end stages of AD. Taken together, these results support a potential role for aberrant control of Akt and PTEN signalling in AD.

Tight junctional abnormality in multiple sclerosis white matter affects all calibres of vessel and is associated with blood-brain barrier leakage and active demyelination

Blood-brain barrier (BBB) hyperpermeability in multiple sclerosis (MS) is associated with lesion pathogenesis and has been linked to pathology in microvascular tight junctions (TJs). This study quantifies the uneven distribution of TJ pathology and its association with BBB leakage. Frozen sections from plaque and normal-appearing white matter (NAWM) in 14 cases were studied together with white matter from six neurological and five normal controls. Using single and double immunofluorescence and confocal microscopy, the TJ-associated protein zonula occludens-1 (ZO-1) was examined across lesion types and tissue categories, and in relation to fibrinogen leakage. Confocal image data sets were analysed for 2198 MS and 1062 control vessels. Significant differences in the incidence of TJ abnormalities were detected between the different lesion types in MS and between MS and control white matter. These were frequent in oil-red O (ORO)+ active plaques, affecting 42% of vessel segments, but less frequent in ORO- inactive plaques (23%), NAWM (13%), and normal (3.7%) and neurological controls (8%). A similar pattern was found irrespective of the vessel size, supporting a causal role for diffusible inflammatory mediators. In both NAWM and inactive lesions, dual labelling showed that vessels with the most TJ abnormality also showed most fibrinogen leakage. This was even more pronounced in active lesions, where 41% of vessels in the highest grade for TJ alteration showed severe leakage. It is concluded that disruption of TJs in MS, affecting both paracellular and transcellular paths, contributes to BBB leakage. TJ abnormality and BBB leakage in inactive lesions suggests either failure of TJ repair or a continuing pathological process. In NAWM, it suggests either pre-lesional change or secondary damage. Clinically inapparent TJ pathology has prognostic implications and should be considered when planning disease-modifying therapy

Equilibrium polymerization of cyclic carbonate oligomers. II. Role of multiple active sites

Ring opening polymerization of bisphenol A polycarbonate is studied by Monte Carlo simulations of a model comprising a fixed number of Lennard-Jones particles and harmonic bonds [J. Chem. Phys. 115, 3895 (2001)]. Bond interchanges produced by a low concentration (0.10%less than or equal toc(a)less than or equal to0.36%) of chemically active particles lead to equilibrium polymerization. There is a continuous transition in both 2D and 3D from unpolymerized cyclic oligomers at low density to a system of linear chains at high density, and the polymeric phase is much more stable in three dimensions than in two. The steepness of the polymerization transition increases rapidly as c(a) decreases, suggesting that it is discontinuous in the limit c(a)-->0. The transition is entropy driven, since the average potential energy increases systematically upon polymerization, and there is a steady decline in the degree of polymerization as the temperature is lowered. The mass distribution functions for open chains and for rings are unimodal, with exponentially decaying tails that can be fitted by Zimm-Schulz functions and simpler exponential forms. (C) 2002 American Institute of Physics.

Packet classification by multi-level cutting of the classification space: An algorithmic-architectural solution for IP packet classification in next generation networks

Traditionally, the Internet provides only a “best-effort” service, treating all packets going to the same destination equally. However, providing differentiated services for different users based on their quality requirements is increasingly becoming a demanding issue. For this, routers need to have the capability to distinguish and isolate traffic belonging to different flows. This ability to determine the flow each packet belongs to is called packet classification. Technology vendors are reluctant to support algorithmic solutions for classification due to their non-deterministic performance. Although CAMs are favoured by technology vendors due to their deterministic high lookup rates, they suffer from the problems of high power dissipation and high silicon cost. This paper provides a new algorithmic-architectural solution for packet classification that mixes CAMs with algorithms based on multi-level cutting the classification space into smaller spaces. The provided solution utilizes the geometrical distribution of rules in the classification space. It provides the deterministic performance of CAMs, support for dynamic updates, and added flexibility for system designers.

Social networks applied to training

In this article, we address the importance and relevance that social networks exhibit in their use as an educational resource.  This relevance relies in the possibility of implementing new learning resources or increasing the level of the participant's connectivity, as well as developing learning communities.  Also, the risk entailed from their use is discussed, especially for the students that have a low technological education or those having excessive confidence on the media.  It is important to highlight that the educational use of social networks is not a simple extension or translation of the student's habitual, recreational use, but that it implies an important change in the roles given to teachers as well as learners; from accommodative learning environments that only encourage memorization to other environments that demand an active, reflective, collaborative and proactive attitude, that require the development/acquisition of technological as well as social abilities, aptitudes and values.  It is also important to highlight that a correct implementation and adequate use will not only foment formal learning, but also informal and non-formal learning.

Social networks and lifelong learning in older people

Various socio-demographic factors are causing our society to coexist every day with a group of elderly population that remains active and inserted into the daily dynamics. However, it is believed that there are certain barriers that make this group of people to not adequately address the technologies and even social networks. The creation of the University Programs for the Elderly (PUM), however, is leading to a new stage, since older people who participate come into contact with all kinds of content and rigor, updating own university education, thus changing the way to tackle the most innovative and different situations. In this study, we analyze what is the knowledge and use of older people, PUM, attending the University of Jaen have of the social networks and the assessment made of the need for these programs. To achieve this, we used a methodology in which qualitative and quantitative processes were articulated, through the analysis of data obtained from interviews and a focus groups with program Aquad 7. The data collected show that there is still some ignorance about social networks by older people, but everyone values their usefulness and necessity. Participants believe that they will be least affected of the risks of these technologies and demand a greater training in these contained within the PUM.

Efficient Path Key Establishment For Wireless Sensor Networks

Key pre-distribution schemes have been proposed as means to overcome Wireless Sensor Networks constraints such as limited communication and processing power. Two sensor nodes can establish a secure link with some probability based on the information stored in their memories though it is not always possible that two sensor nodes may set up a secure link. In this paper, we propose a new approach that elects trusted common nodes called ”Proxies” which reside on an existing secure path linking two sensor nodes. These sensor nodes are used to send the generated key which will be divided into parts (nuggets) according to the number of elected proxies. Our approach has been assessed against previously developed algorithms and the results show that our algorithm discovers proxies more quickly which are closer to both end nodes, thus producing shorter path lengths. We have also assessed the impact of our algorithm on the average time to establish a secure link when the transmitter and receiver of the sensor nodes are ”ON”. The results show the superiority of our algorithm in this regard. Overall, the proposed algorithm is well suited for Wireless Sensor Networks.

Neural network controlled three-phase four-wire shunt active powerfilter

A three-phase four-wire shunt active power filter for harmonic mitigation and reactive power compensation in power systems supplying nonlinear loads is presented. Three adaptive linear neurons are used to tackle the desired three-phase filter current templates. Another feedforward three-layer neural network is adopted to control the output filter compensating currents online. This is accomplished by producing the appropriate switching patterns of the converter's legs IGBTs. Adequate tracking of the filter current references is obtained by this method. The active filter injects the current required to compensate for the harmonic and reactive components of the line currents, Simulation results of the proposed active filter indicate a remarkable improvement in the source current waveforms. This is reflected in the enhancement of the unified power quality index defined. Also, the filter has exhibited quite a high dynamic response for step variations in the load current, assuring its potential for real-time applications