Investigation of potential antibacterial action for postharvest copper treatments of cut Acacia holosericea

The mechanisms of action of Cu 2+ in improving the longevity of cut flowers and foliage have not been elucidated. Possible antimicrobial action of Cu 2+ against stem end and vase solution colonising bacteria was investigated using Cu 2+ treatments optimised for cut Acacia holosericea A. Cunn. ex G. Don foliage stems. These treatments were a 5h pulse with 2.2mM Cu 2+ or a 0.5mM Cu 2+ vase solution versus a deionised water (no Cu 2+) control. Bacterial growth over time was assessed by a standard plate count agar technique and with scanning electron microscopy. Cu 2+ treatments significantly extended the cut foliage vase life. However, they did not have sustained antibacterial activity against stem end or vase solution colonising bacteria. Also, regular recutting of 1-2cm from the stem ends did not substantially improve either cut stem water relations or longevity. The positive effects of Cu 2+ treatments were unaffected by the repeated stem end recutting. It was concluded that the primary mechanism of Cu 2+ was not antibacterial. Moreover, naturally growing vase solution and stem end microbial populations had relatively insignificant effects on cut A. holosericea vase life. Research into alternative mechanisms of Cu 2+ is required. © 2012 Elsevier B.V.

Bustle behind the scenes of action : nemosis as a model for fibroblast inflammatory activation

Wound healing is a complex process that requires an interplay between several cell types. Classically, fibroblasts have been viewed as producers of extracellular matrix, but more recently they have been recognized as orchestrators of the healing response, promoting and directing, inflammation and neovascularization processes. Compared to those from healthy tissue, inflammation-associated fibroblasts display a dramatically altered phenotype and have been described as sentinel cells, able to switch to an immunoregulatory profile on cue. However, the activation mechanism still remains largely uncharacterized. Nemosis is a model for stromal fibroblast activation. When normal human primary fibroblasts are deprived of growth support they cluster, forming multicellular spheroids. Clustering results in upregulation of proinflammatory markers such as cyclooxygenase-2 and secretion of prostaglandins, proteinases, cytokines, and growth factors. Fibroblasts in nemosis induce wound healing and tumorigenic responses in many cell types found in inflammatory and tumor microenvironments. This study investigated the effect of nemotic fibroblasts on two components of the vascular system, leukocytes and endothelium, and characterized the inflammation-promoting responses that arose in these cell types. Fibroblasts in nemosis were found to secrete an array of chemotactic cytokines and attract leukocytes, as well as promote their adhesion to the endothelium. Nuclear factor-kB, the master regulator of many inflammatory responses, is activated in nemotic fibroblasts. Nemotic fibroblasts are known to produce large amounts of hepatocyte growth factor, a motogenic and angiogenic factor. Also, as shown in this study, they produce vascular endothelial growth factor. These two factors induced migratory and sprouting responses in endothelial cells, both required for neovascularization. Nemotic fibroblasts also caused a decrease in the expression of adherens and tight junction components on the surface of endothelial cells. The results allow the conclusion that fibroblasts in nemosis share many similarities with inflammation-associated fibroblasts. Both inflammation and stromal fibroblasts are known to be involved in tumorigenesis and tumor progression. Nemosis may be viewed as a model for stromal fibroblast activation, or it may correlate with cell-cell interactions between adjacent fibroblasts in vivo. Nevertheless, due to nemosis-derived production of proinflammatory cytokines and growth factors, fibroblast nemosis may have therapeutic potential as an inducer of controlled tissue repair. Knowledge of stromal fibroblast activation gained through studies of nemosis, could provide new strategies to control unwanted inflammation and tumor progression.

Assessment of motivation to control alcohol use: The motivational thought frequency and state motivation scales for alcohol control

Introduction The Elaborated Intrusion Theory of Desire holds that desires for functional and dysfunctional goals share a common form. Both are embodied cognitive events, characterised by affective intensity and frequency. Accordingly, we developed scales to measure motivational cognitions for functional goals (Motivational Thought Frequency, MTF; State Motivation, SM), based on the existing Craving Experience Questionnaire (CEQ). When applied to increasing exercise, MTF and SM showed the same three-factor structure as the CEQ (Intensity, Imagery, Availability). The current study tested the internal structure and concurrent validity of the MTF and SM Scales when applied to control of alcohol consumption (MTF-A; SM-A). Methods Participants (N = 417) were adult tertiary students, staff or community members who had recently engaged in high-risk drinking or were currently trying to control alcohol consumption. They completed an online survey comprising the MTF-A, SM-A, Alcohol Use Disorders Identification Test (AUDIT), Readiness to Change Questionnaire (RCQ) and demographics. Results Confirmatory Factor Analysis gave acceptable fit for the MTF-A, but required the loss of one SM-A item, and was improved by intercorrelations of error terms. Higher scores were associated with more severe problems on the AUDIT and with higher Contemplation and Action scores on the RCQ. Conclusions The MTF-A and SM-A show potential as measures of motivation to control drinking. Future research will examine their predictive validity and sensitivity to change. The scales' application to both increasing functional and decreasing dysfunctional behaviours is consistent with EI Theory's contention that both goal types operate in similar ways.

Multidimensionality of Actors in Business Networks: The Influence of Social Action in Pharmacy Networks in Finland

In the markets-as-networks approach business networks are conceived as dynamic actor structures, giving focus to exchange relationships and actors’ capabilities to control and co-ordinate activities and resources. Researchers have shared an understanding that actors’ actions are crucial for the development of business networks and for network dynamics. However, researchers have mainly studied firms as business actors and excluded individuals, although both firms and individuals can be seen as business actors. This focus on firms as business actors has resulted in a paucity of research on human action and the exchange of intangible resources in business networks, e.g. social exchange between individuals in social networks. Consequently, the current conception of business networks fails to appreciate the richness of business actors, the human character of business action and the import of social action in business networks. The central assumption in this study is that business actors are multidimensional and that their specific constitution in any given situation is determined by human interaction in social networks. Multidimensionality is presented as a concept for exploring how business actors act in different situations and how actors simultaneously manage multiple identities: individual, organisational, professional, business and network identities. The study presents a model that describes the multidimensionality of actors in business networks and conceptualises the connection between social exchange and human action in business networks. Empirically the study explores the change that has taken place in pharmaceutical retailing in Finland during recent years. The phenomenon of emerging pharmacy networks is highly contemporary in the Nordic countries, where the traditional license-based pharmacy business is changing. The study analyses the development of two Finnish pharmacy chains, one integrated and one voluntary chain, and the network structures and dynamics in them. Social Network Analysis is applied to explore the social structures within the pharmacy networks. The study shows that emerging pharmacy networks are multifaceted phenomena where political, economic, social, cultural, and historical elements together contribute to the observed changes. Individuals have always been strongly present in the pharmacy business and the development of pharmacy networks provides an interesting example of human actors’ influence in the development of business networks. The dynamics or forces driving the network development can be linked to actors’ own economic and social motives for developing the business. The study highlights the central role of individuals and social networks in the development of the two studied pharmacy networks. The relation between individuals and social networks is reciprocal. The social context of every individual enables multidimensional business actors. The mix of various identities, both individual and collective identities, is an important part of network dynamics. Social networks in pharmacy networks create a platform for exchange and social action, and social networks enable and support business network development.

Gonadotropin regulation of rat ovarian lysosomes: Existence of a hormone specific dual control mechanism

Gonadotropic hormones PMSG (15 IU/rat), FSH (3 mgrg/rat), LH (9 mgrg/rat) and hCG (3 mgrg/rat) were shown to decrease the free cytosolic lysosomal enzymes during the acute phase of hormone action in rat ovaries. When isolated cells from such rats were analyzed for the cathepsin-D activity, the granulosa cells of the ovary showed a reduction in the free as well as in the total lysosomal enzyme activities in response to FSH/PMSG; the stromal and thecal compartment of the ovary showed a reduction only in the free activity in response to hCG/PMSG. The results suggest the presence of two distinct, target cell specific, mechanisms by which the lysosmal activity of the ovary is regulated by gonadotropins.

A single network adaptive critic (SNAC) architecture for optimal control synthesis for a class of nonlinear systems

Even though dynamic programming offers an optimal control solution in a state feedback form, the method is overwhelmed by computational and storage requirements. Approximate dynamic programming implemented with an Adaptive Critic (AC) neural network structure has evolved as a powerful alternative technique that obviates the need for excessive computations and storage requirements in solving optimal control problems. In this paper, an improvement to the AC architecture, called the �Single Network Adaptive Critic (SNAC)� is presented. This approach is applicable to a wide class of nonlinear systems where the optimal control (stationary) equation can be explicitly expressed in terms of the state and costate variables. The selection of this terminology is guided by the fact that it eliminates the use of one neural network (namely the action network) that is part of a typical dual network AC setup. As a consequence, the SNAC architecture offers three potential advantages: a simpler architecture, lesser computational load and elimination of the approximation error associated with the eliminated network. In order to demonstrate these benefits and the control synthesis technique using SNAC, two problems have been solved with the AC and SNAC approaches and their computational performances are compared. One of these problems is a real-life Micro-Electro-Mechanical-system (MEMS) problem, which demonstrates that the SNAC technique is applicable to complex engineering systems.

Optimal control of arrivals to queues with delayed queue length information

We consider discrete-time versions of two classical problems in the optimal control of admission to a queueing system: i) optimal routing of arrivals to two parallel queues and ii) optimal acceptance/rejection of arrivals to a single queue. We extend the formulation of these problems to permit a k step delay in the observation of the queue lengths by the controller. For geometric inter-arrival times and geometric service times the problems are formulated as controlled Markov chains with expected total discounted cost as the minimization objective. For problem i) we show that when k = 1, the optimal policy is to allocate an arrival to the queue with the smaller expected queue length (JSEQ: Join the Shortest Expected Queue). We also show that for this problem, for k greater than or equal to 2, JSEQ is not optimal. For problem ii) we show that when k = 1, the optimal policy is a threshold policy. There are, however, two thresholds m(0) greater than or equal to m(1) > 0, such that mo is used when the previous action was to reject, and mi is used when the previous action was to accept.

Reinforcement Learning With Function Approximation for Traffic Signal Control

We propose, for the first time, a reinforcement learning (RL) algorithm with function approximation for traffic signal control. Our algorithm incorporates state-action features and is easily implementable in high-dimensional settings. Prior work, e. g., the work of Abdulhai et al., on the application of RL to traffic signal control requires full-state representations and cannot be implemented, even in moderate-sized road networks, because the computational complexity exponentially grows in the numbers of lanes and junctions. We tackle this problem of the curse of dimensionality by effectively using feature-based state representations that use a broad characterization of the level of congestion as low, medium, or high. One advantage of our algorithm is that, unlike prior work based on RL, it does not require precise information on queue lengths and elapsed times at each lane but instead works with the aforementioned described features. The number of features that our algorithm requires is linear to the number of signaled lanes, thereby leading to several orders of magnitude reduction in the computational complexity. We perform implementations of our algorithm on various settings and show performance comparisons with other algorithms in the literature, including the works of Abdulhai et al. and Cools et al., as well as the fixed-timing and the longest queue algorithms. For comparison, we also develop an RL algorithm that uses full-state representation and incorporates prioritization of traffic, unlike the work of Abdulhai et al. We observe that our algorithm outperforms all the other algorithms on all the road network settings that we consider.

Towards the concept of hydrodynamic cavitation control

A careful study of the existing literature available in the field of cavitation reveals the potential of ultrasonics as a tool for controlling and, if possible, eliminating certain types of hydrodynamic cavitation through the manipulation of nuclei size present in a flow. A glass venturi is taken to be an ideal device to study the cavitation phenomenon at its throat and its potential control. A piezoelectric transducer, driven at the crystal resonant frequency, is used to generate an acoustic pressure field and is termed an �ultrasonic nuclei manipulator (UNM)�. Electrolysis bubbles serve as artificial nuclei to produce travelling bubble cavitation at the venturi throat in the absence of a UNM but this cavitation is completely eliminated when a UNM is operative. This is made possible because the nuclei, which pass through the acoustic field first, cavitate, collapse violently and perhaps fragment and go into dissolution before reaching the venturi throat. Thus, the potential nuclei for travelling bubble cavitation at the venturi throat seem to be systematically destroyed through acoustic cavitation near the UNM. From the solution to the bubble dynamics equation, it has been shown that the potential energy of a bubble at its maximum radius due to an acoustic field is negligible compared to that for the hydrodynamic field. Hence, even though the control of hydrodynamic macro cavitation achieved in this way is at the expense of acoustic micro cavitation, it can still be considered to be a significant gain. These are some of the first results in this direction.

Flexible implementation of power system corrective topology control

This paper proposes a novel decision making framework for optimal transmission switching satisfying the AC feasibility, stability and circuit breaker (CB) reliability requirements needed for practical implementation. The proposed framework can be employed as a corrective tool in day to day operation planning scenarios in response to potential contingencies. The switching options are determined using an efficient heuristic algorithm based on DC optimal power flow, and are presented in a multi-branch tree structure. Then, the AC feasibility and stability checks are conducted and the CB condition monitoring data are employed to perform a CB reliability and line availability assessment. Ultimately, the operator will be offered multiple AC feasible and stable switching options with associated benefits. The operator can use this information, other operating conditions not explicitly considered in the optimization, and his/her own experience to implement the best and most reliable switching action(s). The effectiveness of the proposed approach is validated on the IEEE-118 bus test system. (C) 2015 Elsevier B.V. All rights reserved.

Probabilistic inference for fast learning in control

A novel framework is provided for very fast model-based reinforcement learning in continuous state and action spaces. It requires probabilistic models that explicitly characterize their levels of condence. Within the framework, exible, non-parametric models are used to describe the world based on previously collected experience. It demonstrates learning on the cart-pole problem in a setting where very limited prior knowledge about the task has been provided. Learning progressed rapidly, and a good policy found after only a small number of iterations.

Robust multiplexed model predictive control

This paper extends the recently developed multiplexed model predictive control (MMPC) concept to ensure satisfaction of hard constraints despite the action of persistent, unknown but bounded disturbances. MMPC uses asynchronous control moves on each input channel instead of synchronised moves on all channels. It offers reduced computation, by dividing the online optimisation into a smaller problem for each channel, and potential performance improvements, as the response to a disturbance is quicker, albeit via only one channel. Robustness to disturbances is introduced using the constraint tightening approach, tailored to suit the asynchronous updates of MMPC and the resulting time-varying optimisations. Numerical results are presented, involving a simple mechanical example and an aircraft control example, showing the potential computational and performance benefits of the new robust MMPC.

Performance of an Ocean Energy Conversion System with DFIG Sensorless Control

The 2009/28/EC Directive requires Member States of the European Union to adopt a National Action Plan for Renewable Energy. In this context, the Basque Energy Board, EVE, is committed to research activities such as the Mutriku Oscillating Water Column plant, OWC. This is an experimental facility whose concept consists of a turbine located in a pneumatic energy collection chamber and a doubly fed induction generator that converts energy extracted by the turbine into a form that can be returned to the network. The turbo-generator control requires a precise knowledge of system parameters and of the rotor angular velocity in particular. Thus, to remove the rotor speed sensor implies a simplification of the hardware that is always convenient in rough working conditions. In this particular case, a Luenberger based observer is considered and the effectiveness of the proposed control is shown by numerical simulations. Comparing these results with those obtained using a traditional speed sensor, it is shown that the proposed solution provides better performance since it increases power extraction in the sense that it allows a more reliable and robust performance of the plant, which is even more relevant in a hostile environment as the ocean.

Temporal and spacial control of RNA stability in the early embryo of Drosophila melanogaster

Early embryogenesis in metazoa is controlled by maternally synthesized products. Among these products, the mature egg is loaded with transcripts representing approximately two thirds of the genome. A subset of this maternal RNA pool is degraded prior to the transition to zygotic control of development. This transfer of control of development from maternal to zygotic products is referred to as the midblastula transition (or MBT). It is believed that the degradation of maternal transcripts is required to terminate maternal control of development and to allow zygotic control of development to begin. Until now this process of maternal transcript degradation and the subsequent timing of the MBT has been poorly understood. I have demonstrated that in the early embryo there are two independent RNA degradation pathways, either of which is sufficient for transcript elimination. However, only the concerted action of both pathways leads to elimination of transcripts with the correct timing, at the MBT. The first pathway is maternally encoded, is triggered by egg activation, and is targeted to specific classes of mRNAs through cis-acting elements in the 3' untranslated region (UTR}. The second pathway is activated 2 hr after fertilization and functions together with the maternal pathway to ensure that transcripts are degraded by the MBT. In addition, some transcripts fail to degrade at select subcellular locations adding an element of spatial control to RNA degradation. The spatial control of RNA degradation is achieved by protecting, or masking, transcripts from the degradation machinery. The RNA degradation and protection events are regulated by distinct cis-elements in the 3' untranslated region (UTR). These results provide the first systematic dissection of this highly conserved process in development and demonstrate that RNA degradation is a novel mechanism used for both temporal and spatial control of development.