aXess: an authoring tool for XML content management

The use of XML for representation of eLearning-content and for automatic generation of different kinds of teaching media from this material is with all its advantages nowadays stateof-the-art. In the last years there have been numerous projects that leveraged XML-based production environments. At the end of the financial advancement the created materials have to be maintained with limited (human) resources. In the majority of cases this is only possible, if the authors care for their teaching material without extensive IT-support. From our point of view there has so far been a lack of intuitive usable XML editors. The prototype of such an XML editor “aXess” is introduced with the intention to encourage a broad discussion about the required features to manage the content of eLearning-materials.

Evaluation of Condition Scoring of Feeder Calves as a Tool for Management and Nutrition

Two experiments were conducted to evaluate the effects of body condition scores of beef calves on performance efficiency and carcass characteristics. In Experiment 1, 111 steer calves were stratified by breed and condition score (CS) and randomly allotted to 14 pens. The study was analyzed as a 2 x 3 factorial design, with two breeds (Angus and Simmental) and three initial CS (4.4, 5.1, and 5.6). In Experiment 2, 76 steer calves were allotted to six pens by CS. The resultant pens averaged 3.9, 4.5, 4.7, 5.0, 5.1, and 5.6 in CS. Calves in both studies were fed a corn-based finishing diet formulated to 13.5% crude protein. All calves were implanted with Synovex- SÒ initially and reimplanted with Revalor-SÒ. In Experiment 1, 29-day dry matter intake (lb/day) increased with CS (17.9, 18.1, and 19.1 for 4.4, 5.1, and 5.6, respectively; p < .04). Daily gain (29 days) tended to decrease with increasing CS (4.19, 3.71, and 3.26; p < .13). Days on feed decreased with increasing CS (185, 180, and 178d; p < .07). In Experiment 2, daily gains also increased with decreasing initial CS for the first 114 days (p < .05) and tended to increase overall (p < .20). In Experiment 1, calves with lower initial CS had less external fat at slaughter (.48, .53, and .61 in. for CS 4.4, 5.1, and 5.6, respectively; p < .05). This effect was also noted at slaughter (p < .10), as well as at 57 days (p < .06) and at 148 days (p < .06) as measured by real-time ultrasound. Measurements of intramuscular fat and marbling were not different in either study. These data suggest that CS of feeder calves may be a useful tool for adjusting energy requirements of calves based on body condition. Also, feeder cattle may be sorted into outcome or management groups earlier than currently practiced using body condition and/or real-time ultrasound.

Dynamic SLA management with forecasting using multi-objective optimization

Cost-efficient operation while satisfying performance and availability guarantees in Service Level Agreements (SLAs) is a challenge for Cloud Computing, as these are potentially conflicting objectives. We present a framework for SLA management based on multi-objective optimization. The framework features a forecasting model for determining the best virtual machine-to-host allocation given the need to minimize SLA violations, energy consumption and resource wasting. A comprehensive SLA management solution is proposed that uses event processing for monitoring and enables dynamic provisioning of virtual machines onto the physical infrastructure. We validated our implementation against serveral standard heuristics and were able to show that our approach is significantly better.

The energy expenditure of 2 Holstein cow strains in an organic grazing system

Until recently, measurements of energy expenditure (EE; herein defined as heat production) in respiration chambers did not account for the extra energy requirements of grazing dairy cows on pasture. As energy is first limiting in most pasture-based milk production systems, its efficient use is important. Therefore, the aim of the present study was to compare EE, which can be affected by differences in body weight (BW), body composition, grazing behavior, physical activity, and milk production level, in 2 Holstein cow strains. Twelve Swiss Holstein-Friesian (HCH; 616 kg of BW) and 12 New Zealand Holstein-Friesian (HNZ; 570 kg of BW) cows in the third stage of lactation were paired according to their stage of lactation and kept in a rotational, full-time grazing system without concentrate supplementation. After adaption, the daily milk yield, grass intake using the alkane double-indicator technique, nutrient digestibility, physical activity, and grazing behavior recorded by an automatic jaw movement recorder were investigated over 7d. Using the (13)C bicarbonate dilution technique in combination with an automatic blood sampling system, EE based on measured carbon dioxide production was determined in 1 cow pair per day between 0800 to 1400 h. The HCH were heavier and had a lower body condition score compared with HNZ, but the difference in BW was smaller compared with former studies. Milk production, grass intake, and nutrient digestibility did not differ between the 2 cow strains, but HCH grazed for a longer time during the 6-h measurement period and performed more grazing mastication compared with the HNZ. No difference was found between the 2 cow strains with regard to EE (291 ± 15.6 kJ) per kilogram of metabolic BW, mainly due to a high between-animal variation in EE. As efficiency and energy use are important in sustainable, pasture-based, organic milk production systems, the determining factors for EE, such as methodology, genetics, physical activity, grazing behavior, and pasture quality, should be investigated and quantified in more detail in future studies.

Comparison of energy expenditure, eating pattern and physical activity of grazing and zero-grazing dairy cows at different time points during lactation

An experiment was conducted to determine the effect of grazing versus zero-grazing on energy expenditure (EE), feeding behaviour and physical activity in dairy cows at different stages of lactation. Fourteen Holstein cows were subjected to two treatments in a repeated crossover design with three experimental series (S1, S2, and S3) reflecting increased days in milk (DIM). At the beginning of each series, cows were on average at 38, 94 and 171 (standard deviation (SD) 10.8) DIM, respectively. Each series consisted of two periods containing a 7-d adaptation and a 7-d collection period each. Cows either grazed on pasture for 16–18.5 h per day or were kept in a freestall barn and had ad libitum access to herbage harvested from the same paddock. Herbage intake was estimated using the double alkane technique. On each day of the collection period, EE of one cow in the barn and of one cow on pasture was determined for 6 h by using the 13C bicarbonate dilution technique, with blood sample collection done either manually in the barn or using an automatic sampling system on pasture. Furthermore, during each collection period physical activity and feeding behaviour of cows were recorded over 3 d using pedometers and behaviour recorders. Milk yield decreased with increasing DIM (P<0.001) but was similar with both treatments. Herbage intake was lower (P<0.01) for grazing cows (16.8 kg dry matter (DM)/d) compared to zero-grazing cows (18.9 kg DM/d). The lowest (P<0.001) intake was observed in S1 and similar intakes were observed in S2 and S3. Within the 6-h measurement period, grazing cows expended 19% more (P<0.001) energy (319 versus 269 kJ/kg metabolic body size (BW0.75)) than zero-grazing cows and differences in EE did not change with increasing DIM. Grazing cows spent proportionally more (P<0.001) time walking and less time standing (P<0.001) and lying (P<0.05) than zero-grazing cows. The proportion of time spent eating was greater (P<0.001) and that of time spent ruminating was lower (P<0.05) for grazing cows compared to zero-grazing cows. In conclusion, lower feed intake along with the unchanged milk production indicates that grazing cows mobilized body reserves to cover additional energy requirements which were at least partly caused by more physical activity. However, changes in cows׳ behaviour between the considered time points during lactation were too small so that differences in EE remained similar between treatments with increasing DIM.

Understanding E-Bike Users' Behaviour, Motives, and Barriers to the Use - An Empirical Study with high Potential for Mobility Management

A representative study among e-bike owners and tenants in Switzerland (n = 1652) provides a deeper understanding of e-bike users characteristics, motives, values, usage behavior, and barriers to the use. In a micro simulation the implications of the findings for the energy demand and CO2 emissions are estimated.

Energy Efficient Multimedia Communications in IEEE 802.11 Networks

During the last decade wireless mobile communications have progressively become part of the people’s daily lives, leading users to expect to be “alwaysbest-connected” to the Internet, regardless of their location or time of day. This is indeed motivated by the fact that wireless access networks are increasingly ubiquitous, through different types of service providers, together with an outburst of thoroughly portable devices, namely laptops, tablets, mobile phones, among others. The “anytime and anywhere” connectivity criterion raises new challenges regarding the devices’ battery lifetime management, as energy becomes the most noteworthy restriction of the end-users’ satisfaction. This wireless access context has also stimulated the development of novel multimedia applications with high network demands, although lacking in energy-aware design. Therefore, the relationship between energy consumption and the quality of the multimedia applications perceived by end-users should be carefully investigated. This dissertation addresses energy-efficient multimedia communications in the IEEE 802.11 standard, which is the most widely used wireless access technology. It advances the literature by proposing a unique empirical assessment methodology and new power-saving algorithms, always bearing in mind the end-users’ feedback and evaluating quality perception. The new EViTEQ framework proposed in this thesis, for measuring video transmission quality and energy consumption simultaneously, in an integrated way, reveals the importance of having an empirical and high-accuracy methodology to assess the trade-off between quality and energy consumption, raised by the new end-users’ requirements. Extensive evaluations conducted with the EViTEQ framework revealed its flexibility and capability to accurately report both video transmission quality and energy consumption, as well as to be employed in rigorous investigations of network interface energy consumption patterns, regardless of the wireless access technology. Following the need to enhance the trade-off between energy consumption and application quality, this thesis proposes the Optimized Power save Algorithm for continuous Media Applications (OPAMA). By using the end-users’ feedback to establish a proper trade-off between energy consumption and application performance, OPAMA aims at enhancing the energy efficiency of end-users’ devices accessing the network through IEEE 802.11. OPAMA performance has been thoroughly analyzed within different scenarios and application types, including a simulation study and a real deployment in an Android testbed. When compared with the most popular standard power-saving mechanisms defined in the IEEE 802.11 standard, the obtained results revealed OPAMA’s capability to enhance energy efficiency, while keeping end-users’ Quality of Experience within the defined bounds. Furthermore, OPAMA was optimized to enable superior energy savings in multiple station environments, resulting in a new proposal called Enhanced Power Saving Mechanism for Multiple station Environments (OPAMA-EPS4ME). The results of this thesis highlight the relevance of having a highly accurate methodology to assess energy consumption and application quality when aiming to optimize the trade-off between energy and quality. Additionally, the obtained results based both on simulation and testbed evaluations, show clear benefits from employing userdriven power-saving techniques, such as OPAMA, instead of IEEE 802.11 standard power-saving approaches.

The Role of Forest Soils in a Northern New England Effluent Management System

The Carrabassett Valley Sanitary District in Carrabassett Valley, Maine has utilized both a forest spray irrigation system and a Snowfluent™ system for the treatment of their wastewater effluent. This study was designed to evaluate potential changes in soil properties after approximately 20 years of treatment in the forested spray irrigation site and three years of treatment in the field Snowfluent™ site. In addition, grass yield and composition were evaluated on the field study sites. After treatment with effluent or Snowfluent™, soils showed an increase in soil exchangeable Ca, Mg, Na, and K, base saturation, and pH. While most constituents were higher in treated soils, available P was lower in treated soils compared to the controls. This difference was attributed to higher rates of P mineralization from soil organic matter due to an irrigation effect of the treatment, depleting available P pools despite the P addition with the treatment. Most of the differences due to treatment were greatest at the surface and diminished with depth. Depth patterns in soil properties mostly reflected the decreasing influence of organic matter and its decomposition products with depth as evidenced by significantly higher total C in the surface compared to lower horizons. There were decreasing concentrations of total N, and exchangeable or extractable Ca, Mg, Na, K, Mn, Zn, and P with depth. In addition, there was decreasing BS with depth, driven primarily by declining exchangeable Ca and Mg. Imgation with Snowfluent™ altered the chemical composition of the grass on the site. All element concentrations were significantly higher in the grass foliage except for Ca. The differences were attributed to the additional nutrients and moisture derived from the Snowfluent™. The use of forest spray imgation and Snowfluent™ as a wastewater treatment strategy appears to work well. The soil and vegetation were able to retain most of the applied nutrients, and do not appear to be moving toward saturation. Vegetation management may be a key tool for managing nutrient accumulation on the grass sites as the system ages.

Complementary and Alternative Medicine and Pain Management

Over the past several years, there has been a growing interest in CAM therapies at UCHC. There are doctors, nurses, researchers and students all actively learning about, researching and using CAM modalities. Among them is Dr. Mitch Kennedy, the first Naturopathic Physician to treat patients at the University of Connecticut Health Center.

Evaluation of the influence of toll systems on energy consumption and CO2 emissions: A case study of a Spanish highway

This paper studies the energy consumption and subsequent CO2 emissions of road highway transportation under three toll systems in Spain for four categories of vehicles: cars, vans, buses and articulated trucks. The influence of toll systems is tested for a section of AP-41 highway between Toledo and Madrid. One system is free flow, other is traditional stop and go and the last toll system operates with an electronic toll collection (ETC) technology. Energy consumption and CO2 emissions were found to be closely related to vehicle mass, wind exposure, engine efficiency and acceleration rate. These parameters affect, directly or indirectly, the external forces which determine the energy consumption. Reducing the magnitude of these forces through an appropriate toll management is an important way of improving the energy performance of vehicles. The type of toll system used can have a major influence on the energy efficiency of highway transportation and therefore it is necessary to consider free flow.

Accident Management Actions In An Upper-Head Small-Break Loss-Of-Coolant Accident With High-Pressure Safety Injection Failed

Since the Three Mile Island accident, an important focus of pressurized water reactor (PWR) transient analyses has been a small-break loss-of-coolant accident (SBLOCA). In 2002, the discovery of thinning of the vessel head wall at the Davis Besse nuclear power plant reactor indicated the possibility of an SBLOCA in the upper head of the reactor vessel as a result of circumferential cracking of a control rod drive mechanism penetration nozzle - which has cast even greater importance on the study of SBLOCAs. Several experimental tests have been performed at the Large Scale Test Facility to simulate the behavior of a PWR during an upper-head SBLOCA. The last of these tests, Organisation for Economic Co-operation and Development Nuclear Energy Agency Rig of Safety Assessment (OECD/NEA ROSA) Test 6.1, was performed in 2005. This test was simulated with the TRACE 5.0 code, and good agreement with the experimental results was obtained. Additionally, a broad analysis of an upper-head SBLOCA with high-pressure safety injection failed in a Westinghouse PWR was performed taking into account different accident management actions and conditions in order to check their suitability. This issue has been analyzed also in the framework of the OECD/NEA ROSA project and the Code Applications and Maintenance Program (CAMP). The main conclusion is that the current emergency operating procedures for Westinghouse reactor design are adequate for these kinds of sequences, and they do not need to be modified.

Performance of a transmutation advanced device for sustainable energy application

Preliminary studies have been performed to design a device for nuclear waste transmutation and hydrogen generation based on a gas-cooled pebble bed accelerator driven system, TADSEA (Transmutation Advanced Device for Sustainable Energy Application). In previous studies we have addressed the viability of an ADS Transmutation device that uses as fuel wastes from the existing LWR power plants, encapsulated in graphite in the form of pebble beds, cooled by helium which enables high temperatures (in the order of 1200 K), to generate hydrogen from water either by high temperature electrolysis or by thermochemical cycles. For designing this device several configurations were studied, including several reflectors thickness, to achieve the desired parameters, the transmutation of nuclear waste and the production of 100 MW of thermal power. In this paper new studies performed on deep burn in-core fuel management strategy for LWR waste are presented. The fuel cycle on TADSEA device has been analyzed based on both: driven and transmutation fuel that had been proposed by the General Atomic design of a gas turbine-modular helium reactor. The transmutation results of the three fuel management strategies, using driven, transmutation and standard LWR spent fuel were compared, and several parameters describing the neutron performance of TADSEA nuclear core as the fuel and moderator temperature reactivity coefficients and transmutation chain, are also presented

An Efficient Multiple Object Detection and Tracking Framework for Automatic Counting and Video Surveillance Applications

Automatic visual object counting and video surveillance have important applications for home and business environments, such as security and management of access points. However, in order to obtain a satisfactory performance these technologies need professional and expensive hardware, complex installations and setups, and the supervision of qualified workers. In this paper, an efficient visual detection and tracking framework is proposed for the tasks of object counting and surveillance, which meets the requirements of the consumer electronics: off-the-shelf equipment, easy installation and configuration, and unsupervised working conditions. This is accomplished by a novel Bayesian tracking model that can manage multimodal distributions without explicitly computing the association between tracked objects and detections. In addition, it is robust to erroneous, distorted and missing detections. The proposed algorithm is compared with a recent work, also focused on consumer electronics, proving its superior performance.

Statistical Machine Learning for Automatic Assessment of Physical Activity Intensity Using Multi-axial Accelerometry and Heart Rate

This work explores the automatic recognition of physical activity intensity patterns from multi-axial accelerometry and heart rate signals. Data collection was carried out in free-living conditions and in three controlled gymnasium circuits, for a total amount of 179.80 h of data divided into: sedentary situations (65.5%), light-to-moderate activity (17.6%) and vigorous exercise (16.9%). The proposed machine learning algorithms comprise the following steps: time-domain feature definition, standardization and PCA projection, unsupervised clustering (by k-means and GMM) and a HMM to account for long-term temporal trends. Performance was evaluated by 30 runs of a 10-fold cross-validation. Both k-means and GMM-based approaches yielded high overall accuracy (86.97% and 85.03%, respectively) and, given the imbalance of the dataset, meritorious F-measures (up to 77.88%) for non-sedentary cases. Classification errors tended to be concentrated around transients, what constrains their practical impact. Hence, we consider our proposal to be suitable for 24 h-based monitoring of physical activity in ambulatory scenarios and a first step towards intensity-specific energy expenditure estimators

Sensitivity of a distributed temperature-radiation index melt model based on AWS observations and surface energy balance fluxes, Hurd Peninsula glaciers, Livingston Island, Antarctica

We use an automatic weather station and surface mass balance dataset spanning four melt seasons collected on Hurd Peninsula Glaciers, South Shetland Islands, to investigate the point surface energy balance, to determine the absolute and relative contribution of the various energy fluxes acting on the glacier surface and to estimate the sensitivity of melt to ambient temperature changes. Long-wave incoming radiation is the main energy source for melt, while short-wave radiation is the most important flux controlling the variation of both seasonal and daily mean surface energy balance. Short-wave and long-wave radiation fluxes do, in general, balance each other, resulting in a high correspondence between daily mean net radiation flux and available melt energy flux. We calibrate a distributed melt model driven by air temperature and an expression for the incoming short-wave radiation. The model is calibrated with the data from one of the melt seasons and validated with the data of the three remaining seasons. The model results deviate at most 140 mm w.e. from the corresponding observations using the glaciological method. The model is very sensitive to changes in ambient temperature: a 0.5 ◦ C increase results in 56 % higher melt rates.