The shallow atmospheric coal fired fluidized-bed combustor furnace

Bibliography: leaves 196-216.[Not copying properly] The fluidized bed combustor furnace is considered as being made up of two zones, the fluidized bed itself and an upper free-board zone for the disengagement of ejected particles and in which further combustion may take. place simultaneously with the radiative transfer of heat to the surrounding walls. A general review of the literature pertaining to the combustion of coal in a fluidized bed of inert. particles as well as the transfer of heat from the fluidized bed to immersed cooling surfaces is presented. In view of the fluidized bed furnace incorporating the freeboard region, a review of furnace design methods is also presented. The status of research and development in various parts of the world •is considered with particular reference to the generation of steam by means of the combustion of coal in an atmospheric fluidized bed combustion unit

B2B analytics in the airline market: Harnessing the power of consumer big data

This paper utilizes market-level data to explore the relative performance of individual companies amongst defined competitors. We show the potential of using consumer clickstream data, an important type of big data, to create a new set of B2B analytical frameworks. In the markets where complex interactions between competitors, search intermediaries and consumers create a network, B2B relationships can be inferred from consumer search patterns, and can then be modeled to gauge the online performance. A commercial dataset from ComScore's US panel of one million users is used to illustrate a new approach to measure and evaluate the online performance of competitors in the US airline market. The methodology and associated performance framework demonstrate the potential for new forms of market intelligence based on the visualization of market networks, online performance calculated from matrix algorithms, the measurement of the impact of search intermediaries, and the identification of latent relationships. This research makes theoretical and empirical contributions to the debate on the use of big data for B2B market analytics. B2B managers can use this approach to extend their network horizon from an egocentric to a network view of competition and map out their competitive landscape from the perspective of the customer

Examining the dark force consequences of AI as a new actor in B2B relationships

Artificial intelligence (AI) in industrial marketing has seen significant research attention through various theoretical lenses with an emerging thread examining the dark side effects of AI. Thirty-four semi-structured interviews were conducted with buyers and suppliers of AI marketing solutions to investigate the consequences of AI ‘dark forces’ on B2B relationships. We posit AI as a new actor that has blurred the lines of the actors-resources-activities model. Findings show AI is now considered a new actor within B2B networks wielding dark force consequences such as algorithmic gatekeeping, which initiates dehumanization effects. In addition, AI is reliant on access to datasets which drives up resource costs. A lack of accountability of AI marketing solutions leads to opportunistic behaviours compromising actor relationships. Our conceptual model maps our understanding of the dark force consequences underpinning theoretical and managerial implications and recommendations for increased awareness and mitigation of dark forces

Iron chelators inhibit amyloid-beta-induced production of lipocalin 2 in cultured astrocytes

Lipocalin 2 (Lcn2) has been implicated to play a role in various neurodegenerative diseases, and normalizing its overexpression may be of therapeutic potential. Iron chelators were found to reduce Lcn2 levels in certain animal models of CNS injury. Focusing on Alzheimer's disease (AD), we found that the iron chelators deferoxamine and deferiprone inhibited amyloid-β (Aβ)-induced Lcn2 production in cultured primary astrocytes. Accordingly, Aβ-exposure increased astrocytic ferritin production, indicating the possibility that Aβ induces iron accumulation in astrocytes. This effect was not significantly modulated by Lcn2. Known neuroprotective effects of iron chelators may rely in part on normalization of Lcn2 levels

Lipocalin 2 as a link between ageing, risk factor conditions and age-related brain diseases

Chronic (neuro)inflammation plays an important role in many age-related central nervous system (CNS) diseases, including Alzheimer's disease, Parkinson's disease and vascular dementia. Inflammation also characterizes many conditions that form a risk factor for these CNS disorders, such as physical inactivity, obesity and cardiovascular disease. Lipocalin 2 (Lcn2) is an inflammatory protein shown to be involved in different age-related CNS diseases, as well as risk factor conditions thereof. Lcn2 expression is increased in the periphery and the brain in different age-related CNS diseases and also their risk factor conditions. Experimental studies indicate that Lcn2 contributes to various neuropathophysiological processes of age-related CNS diseases, including exacerbated neuroinflammation, cell death and iron dysregulation, which may negatively impact cognitive function. We hypothesize that increased Lcn2 levels as a result of age-related risk factor conditions may sensitize the brain and increase the risk to develop age-related CNS diseases. In this review we first provide a comprehensive overview of the known functions of Lcn2, and its effects in the CNS. Subsequently, this review explores Lcn2 as a potential (neuro)inflammatory link between different risk factor conditions and the development of age-related CNS disorders. Altogether, evidence convincingly indicates Lcn2 as a key constituent in ageing and age-related brain diseases

Targeting TNFR2 as a novel therapeutic strategy for Alzheimer's disease

Alzheimer’s disease (AD) is a progressive neurodegenerative disorder and the most common cause of dementia. Accumulating experimental evidence shows the important linkage between tumor necrosis factor-α (TNF) and AD, but the exact role of TNF in AD is still not completely understood. Although TNF-inhibitors are successfully used for treating several diseases, total inhibition of TNF can cause side effects, particularly in neurological diseases. This is attributed to the opposing roles of the two TNF receptors. TNF receptor 1 (TNFR1) predominantly mediates inflammatory and pro-apoptotic signaling pathways, whereas TNF receptor 2 (TNFR2) is neuroprotective and promotes tissue regeneration. Therefore, the specific activation of TNFR2 signaling, either by directly targeting TNFR2 via TNFR2 agonists or by blocking TNFR1 signaling with TNFR1-selective antagonists, seems a promising strategy for AD therapy. This mini-review discusses the involvement of TNFR2 and its signaling pathway in AD and outlines its potential application as therapeutic target. A better understanding of the function of TNFR2 may lead to the development of a treatment for AD

Lipocalin 2 contributes to brain iron dysregulation but does not affect cognition, plaque load, and glial activation in the J20 Alzheimer mouse model

BackgroundLipocalin 2 (Lcn2) is an acute-phase protein implicated in multiple neurodegenerative conditions. Interestingly, both neuroprotective and neurodegenerative effects have been described for Lcn2. Increased Lcn2 levels were found in human post-mortem Alzheimer (AD) brain tissue, and in vitro studies indicated that Lcn2 aggravates amyloid--induced toxicity. However, the role of Lcn2 has not been studied in an in vivo AD model. Therefore, in the current study, the effects of Lcn2 were studied in the J20 mouse model of AD.MethodsJ20 mice and Lcn2-deficient J20 (J20xLcn2 KO) mice were compared at the behavioral and neuropathological level.ResultsJ20xLcn2 KO and J20 mice presented equally strong AD-like behavioral changes, cognitive impairment, plaque load, and glial activation. Interestingly, hippocampal iron accumulation was significantly decreased in J20xLcn2 KO mice as compared to J20 mice.ConclusionsLcn2 contributes to AD-like brain iron dysregulation, and future research should further explore the importance of Lcn2 in AD

An empirical investigation of Network-Oriented Behaviors in Business-to-Business Markets

This study is concerned with the extent to which network-oriented behaviors directly and/or indirectly affect firm performance. It argues that a firm's interaction behaviors in relation to an embedded network structure are key mechanisms that facilitate the development of important organizational capabilities in dealing with business partners. Such network-oriented behaviors, which are aimed at affecting the position of a company in the network, are consequently important drivers of firm performance, rather than the network structure alone. We develop a conceptual model that captures network-oriented behaviors as a driving force of firm performance in relation to three other key organizational behaviors, i.e., customer-oriented, competitor-oriented and relationship-oriented behaviors. We test the hypothesized model using a dataset of 354 responses collected via an on-line questionnaire from UK managers, whose organizations operate in business-to-business markets in either the manufacturing or services sectors. This study provides four key findings. First, a firm's networkoriented behaviors positively affect the development of customer-oriented and competitor-oriented behaviors. Secondly, they also foster relationship coordination with its important business partners within the network. Thirdly, the effective management of the firm's portfolio of relationships is found to mediate the positive impact of network-oriented behaviors on firm profitability. Lastly, closeness to end-users amplifies the positive effect of network-oriented behaviors on relationship portfolio effectiveness