Modeling nitrous oxide emissions from irrigated agriculture : testing DayCent with high-frequency measurements

A unique high temporal frequency dataset from an irrigated cotton-wheat rotation was used to test the agroecosystem model DayCent to simulate daily N2O emissions from sub-tropical vertisols under different irrigation intensities. DayCent was able to simulate the effect of different irrigation intensities on N2O fluxes and yield, although it tended to overestimate seasonal fluxes during the cotton season. DayCent accurately predicted soil moisture dynamics and the timing and magnitude of high fluxes associated with fertilizer additions and irrigation events. At the daily scale we found a good correlation of predicted vs. measured N2O fluxes (r2 = 0.52), confirming that DayCent can be used to test agricultural practices for mitigating N2O emission from irrigated cropping systems. A 25 year scenario analysis indicated that N2O losses from irrigated cotton-wheat rotations on black vertisols in Australia can be substantially reduced by an optimized fertilizer and irrigation management system (i.e. frequent irrigation, avoidance of excessive fertiliser application), while sustaining maximum yield potentials.

What information is necessary to assess the environmental impacts of deconstruction?

4D modeling - the simulation and visualisation of the construction process - is now a common method used during the building construction process with reasonable support from existing software. The goal of this paper is to examine the information needs required to model the deconstruction/demolition process of a building. The motivation is the need to reduce the impacts on the local environment during the deconstruction process. The focus is on the definition and description of the activities to remove building components and on the assessment of the noise, dust and vibration implications of these activities on the surrounding environment. The outcomes of the research are: i. requirements specification for BIM models to support operational deconstruction process planning, ii. algorithms for augmenting the BIM with the derived information necessary to automate planning of the deconstruction process with respect to impacts on the surrounding environment, iii. algorithms to build naive deconstruction activity schedules.

Scleral matrix metalloproteinases, serine proteinase activity and hydrational capacity are increased in myopia induced by retinal image degradation

In the avian model of myopia, retinal image degradation quickly leads to ocular enlargement. We now give evidence that regionally specific changes in ocular size are correlated with both biomechanical indices of scleral remodeling, e.g. hydration capacity and with biochemical changes in proteinase activities. The latter include a 72 kDa matrix metalloproteinase (putatively MMP-2), other gelatin-binding MMPs, an acid pH MMP and a serine protease. Specifically, we have found that increases in scleral hydrational capacity parallel increases in collagen degrading activities. Gelatin zymography reveals that eyes with 7 days of retinal image degradation have elevated levels (1.4-fold) of gelatinolytic activities at 72 and 67 kDa M(r) in equatorial and posterior pole regions of the sclera while, after 14 days of treatment, increases are no longer apparent. Lower M(r) zymographic activities at 50, 46 and 37 kDa M(r) are collectively increased in eyes treated for both 7 and 14 days (1.4- and 2.4-fold respectively) in the equator and posterior pole areas of enlarging eyes. Western blot analyses of scleral extracts with an antibody to human MMP-2 reveals immunoreactive bands at 65, 30 and 25 kDa. Zymograms incubated under slightly acidic conditions reveal that, in enlarging eyes, MMP activities at 25 and 28 kDa M(r) are increased in scleral equator and posterior pole (1.6- and 4.5-fold respectively). A TIMP-like protein is also identified in sclera and cornea by Western blot analysis. Finally, retinal-image degradation also increases (~2.6-fold) the activity of a 23.5 kDa serine proteinase in limbus, equator and posterior pole sclera that is inhibited by aprotinin and soybean trypsin inhibitor. Taken together, these results indicate that eye growth induced by retinal-image degradation involves increases in the activities of multiple scleral proteinases that could modify the biomechanical properties of scleral structural components and contribute to tissue remodeling and growth.

Modeling and sensorless direct torque and flux control of a dual-airgap axial flux permanent-magnet machine with field-weakening operation

This paper presents the modeling and motion-sensorless direct torque and flux control of a novel dual-airgap axial-flux permanent-magnet machine optimized for use in flywheel energy storage system (FESS) applications. Independent closed-loop torque and stator flux regulation are performed in the stator flux ( x-y) reference frame via two PI controllers. This facilitates fast torque dynamics, which is critical as far as energy charging/discharging in the FESS is concerned. As FESS applications demand high-speed operation, a new field-weakening algorithm is proposed in this paper. Flux weakening is achieved autonomously once the y-axis voltage exceeds the available inverter voltage. An inherently speed sensorless stator flux observer immune to stator resistance variations and dc-offset effects is also proposed for accurate flux and speed estimation. The proposed observer eliminates the rotary encoder, which in turn reduces the overall weight and cost of the system while improving its reliability. The effectiveness of the proposed control scheme has been verified by simulations and experiments on a machine prototype.

Modeling and position-sensorless control of a dual-airgap axial flux permanent magnet machine for flywheel energy storage systems

This paper presents the modeling and position-sensorless vector control of a dual-airgap axial flux permanent magnet (AFPM) machine optimized for use in flywheel energy storage system (FESS) applications. The proposed AFPM machine has two sets of three-phase stator windings but requires only a single power converter to control both the electromagnetic torque and the axial levitation force. The proper controllability of the latter is crucial as it can be utilized to minimize the vertical bearing stress to improve the efficiency of the FESS. The method for controlling both the speed and axial displacement of the machine is discussed. An inherent speed sensorless observer is also proposed for speed estimation. The proposed observer eliminates the rotary encoder, which in turn reduces the overall weight and cost of the system while improving its reliability. The effectiveness of the proposed control scheme has been verified by simulations and experiments on a prototype machine.

Modeling and analysis of a novel variable-speed cage induction generator

This paper introduces a novel cage induction generator and presents a mathematical model, through which its behavior can be accurately predicted. The proposed generator system employs a three-phase cage induction machine and generates single-phase and constant-frequency electricity at varying rotor speeds without an intermediate inverter stage. The technique uses any one of the three stator phases of the machine as the excitation winding and the remaining two phases, which are connected in series, as the power winding. The two-series-connected-and-one-isolated (TSCAOI) phase winding configuration magnetically decouples the two sets of windings, enabling independent control. Electricity is generated through the power winding at both sub- and super-synchronous speeds with appropriate excitation to the isolated single winding at any frequency of generation. A dynamic mathematical model, which accurately predicts the behavior of the proposed generator, is also presented and implemented in MATLAB/Simulink. Experimental results of a 2-kW prototype generator under various operating conditions are presented, together with theoretical results, to demonstrate the viability of the TSCAOI power generation. The proposed generator is simple and capable of both storage and retrieval of energy through its excitation winding and is expected to be suitable for applications, such as small wind turbines and microhydro systems.

Why are early maturing girls less active? Links between pubertal development, psychological well-being, and physical activity among girls at ages 11 and 13

Previous research has shown that early maturing girls at age I I have lower subsequent physical activity at age 13 in comparison to later maturing girls. Possible reasons for this association have not been assessed. This study examines girls' psychological response to puberty and their enjoyment of physical activity as intermediary factors linking pubertal maturation and physical activity. Participants included 178 girls who were assessed at age 11, of whom 168 were reassessed at age 13. All participants were non-Hispanic white and resided in the US. Three measures of pubertal development were obtained at age I I including Tanner breast stage, estradiol levels, and mothers' reports of girls' development on the Pubertal Development Scale (PDS). Measures of psychological well-being at ages I I and 13 included depression, global self-worth, perceived athletic competence, maturation fears, and body esteem. At age 13, girls' enjoyment of physical activity was assessed using the Physical Activity Enjoyment Scale and their daily minutes of moderate-to-vigorous physical activity (MVPA) were assessed using objective monitoring. Structural Equation Modeling was used to assess direct and indirect pathways between pubertal development at age I I and MVPA at age 13. In addition to a direct effect of pubertal development on MVPA, indirect effects were found for depression, global self-worth and maturity fears controlling for covariates. In each instance, more advanced pubertal development at age I I was associated with lower psychological wellbeing at age 13, which predicted lower enjoyment of physical activity at age 13 and in turn lower MVPA. Results from this study suggest that programs designed to increase physical activity among adolescent girls should address the self-consciousness and discontent that girls' experience with their bodies during puberty, particularly if they mature earlier than their peers, and identify activities or settings that make differences in body shape less conspicuous.

University of Glasgow at ImageCLEFPhoto 2009 : optimising similarity and diversity in image retrieval

In this paper we describe the approaches adopted to generate the runs submitted to ImageCLEFPhoto 2009 with an aim to promote document diversity in the rankings. Four of our runs are text based approaches that employ textual statistics extracted from the captions of images, i.e. MMR [1] as a state of the art method for result diversification, two approaches that combine relevance information and clustering techniques, and an instantiation of Quantum Probability Ranking Principle. The fifth run exploits visual features of the provided images to re-rank the initial results by means of Factor Analysis. The results reveal that our methods based on only text captions consistently improve the performance of the respective baselines, while the approach that combines visual features with textual statistics shows lower levels of improvements.

Images inside a reflecting spherical surface with possible application in astronomy

This report studies an algebraic equation whose solution gives the image system of a source of light as seen by an observer inside a reflecting spherical surface. The equation is looked at numerically using GeoGebra. Under the hypothesis that our galaxy is enveloped by a reflecting interface this becomes a possible model for many mysterious extra galactic observations.

Graphene and carbon nanotubes from arc plasmas : experiment and plasma modeling

Graphene and carbon nanotubes are the most promising nanomaterials for application in various modern nanodevices. The successful production of the nanotubes and graphene in a single process was achieved by using a magnetically enhanced arc discharge in helium atmosphere between carbon and metal electrodes. A 3-D fluid model has been used to investigate the discharge parameters.

Mathematical modeling of the cancer cell’s control circuitry : paving the way to individualized therapeutic strategies

Cancer is a disease of signal transduction in which the dysregulation of the network of intracellular and extracellular signaling cascades is sufficient to thwart the cells finely-tuned biochemical control mechanisms. A keen interest in the mathematical modeling of cell signaling networks and the regulation of signal transduction has emerged in recent years, and has produced a glimmer of insight into the sophisticated feedback control and network regulation operating within cells. In this review, we present an overview of published theoretical studies on the control aspects of signal transduction, emphasizing the role and importance of mechanisms such as ‘ultrasensitivity’ and feedback loops. We emphasize that these exquisite and often subtle control strategies represent the key to orchestrating ‘simple’ signaling behaviors within the complex intracellular network, while regulating the trade-off between sensitivity and robustness to internal and external perturbations. Through a consideration of these apparent paradoxes, we explore how the basic homeostasis of the intracellular signaling network, in the face of carcinogenesis, can lead to neoplastic progression rather than cell death. A simple mathematical model is presented, furnishing a vivid illustration of how ‘control-oriented’ models of the deranged signaling networks in cancer cells may enucleate improved treatment strategies, including patient-tailored combination therapies, with the potential for reduced toxicity and more robust and potent antitumor activity.

Degradation modeling and monitoring of machines using operation-specific hidden Markov models

In this paper, a novel data-driven approach to monitoring of systems operating under variable operating conditions is described. The method is based on characterizing the degradation process via a set of operation-specific hidden Markov models (HMMs), whose hidden states represent the unobservable degradation states of the monitored system while its observable symbols represent the sensor readings. Using the HMM framework, modeling, identification and monitoring methods are detailed that allow one to identify a HMM of degradation for each operation from mixed-operation data and perform operation-specific monitoring of the system. Using a large data set provided by a major manufacturer, the new methods are applied to a semiconductor manufacturing process running multiple operations in a production environment.

Modeling of protein signaling networks in clinical proteomics

Molecular interactions that underlie pathophysiological states are being elucidated using techniques that profile proteomicend points in cellular systems. Within the field of cancer research, protein interaction networks play pivotal roles in the establishment and maintenance of the hallmarks of malignancy, including cell division, invasion, and migration. Multiple complementary tools enable a multifaceted view of how signal protein pathway alterations contribute to pathophysiological states.One pivotal technique is signal pathway profiling of patient tissue specimens. This microanalysis technology provides a proteomic snapshot at one point in time of cells directly procured from the native context of a tumor micro environment. To study the adaptive patterns of signal pathway events over time, before and after experimental therapy, it is necessary to obtain biopsies from patients before, during, and after therapy. A complementary approach is the profiling of cultured cell lines with and without treatment. Cultured cell models provide the opportunity to study short-term signal changes occurring over minutes to hours. Through this type of system, the effects of particular pharmacological agents may be used to test the effects of signal pathway inhibition or activation on multiple endpoints within a pathway. The complexity of the data generated has necessitated the development of mathematical models for optimal interpretation of interrelated signaling pathways. In combination,clinical proteomic biopsy profiling, tissue culture proteomic profiling, and mathematical modeling synergistically enable a deeper understanding of how protein associations lead to disease states and present new insights into the design of therapeutic regimens.