Compact Representation of Association Rule

Bitmap is an extremely efficient way of representing data, but the drawback is that the order of data is fixed in a bitmap. Granular computing is a new theory that frees the bitmap method from fixed order of data in the same manner as linear algebra frees the matrix theory from a fixed basis. To obtain meaningful information using data mining techniques has been a central idea in recent database applications [2]. One of the core techniques in data mining is to find associations (undirected association rules) between attribute values [4]. The complexity of finding associations is often very high. In this work, a data warehouse is constructed utilizing bitmap fundamentals. Classic method of obtaining association rules is implemented along with the granular computing method of obtaining association rules. The performances from classic method and granular computing method is carefully analyzed and compared

Actin3 promoter reveals undulating F-actin bundles at shanks and dynamic F-actin meshworks at tips of tip-growing pollen tubes

The dynamic actin cytoskeleton of pollen tubes is both the driver of the tip growth and the organizer of cell polarity. In order to understand this fast re-arranging cytoskeletal system, we need reliable constructs expressed under relevant promoters. Here we are reporting that the Lifeact reporter, expressed under the pollen-specific Actin3 promoter, visualizes very dynamic F-actin elements both in germinating pollen grains and tip-growing pollen tubes. Importantly, we have documented very active actin polymerization at the cell periphery, especially in the bulging area during pollen germination and in the apical clear zone. Expression of the Lifeact reporter under control of the pollen-specific Actin3 promoter revealed 2 new aspects: (i) long F-actin bundles in pollen tube shanks are dynamic, showing undulating movements, (ii) subapical ‘actin collars’ or ‘fringes’ are absent

Neural network modelling of RC deep beam shear strength

YesA 9 x 18 x 1 feed-forward neural network (NN) model trained using a resilient back-propagation algorithm and early stopping technique is constructed to predict the shear strength of deep reinforced concrete beams. The input layer covering geometrical and material properties of deep beams has nine neurons, and the corresponding output is the shear strength. Training, validation and testing of the developed neural network have been achieved using a comprehensive database compiled from 362 simple and 71 continuous deep beam specimens. The shear strength predictions of deep beams obtained from the developed NN are in better agreement with test results than those determined from strut-and-tie models. The mean and standard deviation of the ratio between predicted capacities using the NN and measured shear capacities are 1.028 and 0.154, respectively, for simple deep beams, and 1.0 and 0.122, respectively, for continuous deep beams. In addition, the trends ascertained from parametric study using the developed NN have a consistent agreement with those observed in other experimental and analytical investigations

Application of Plasticity Theory to Reinforced Concrete Deep Beams

yesThis paper reviews the application of the plasticity theory to reinforced concrete deep beams. Both the truss analogy and mechanism approach were employed to predict the capacity of reinforced concrete deep beams. In addition, most current codes of practice, for example Eurocode 1992 and ACI 318-05, recommend the strut-and-tie model for designing reinforced concrete deep beams. Compared with methods based on empirical or semi-empirical equations, the strut-and-tie model and mechanism analyses are more rational, adequately accurate and sufficiently simple for estimating the load capacity of reinforced concrete deep beams. However, there is a problem of selecting the effectiveness factor of concrete as reflected in the wide range of values reported in the literature for deep beams

"From the moment i wake up i will use it?every day, very hour": A qualitative study on the patterns of adolescents' mobile touch screen device use from adolescent and parent perspectives

Background: The use of mobile touch screen devices, e.g. smartphones and tablet computers, has become increasingly prevalent among adolescents. However, little is known about how adolescents use these devices and potential influences on their use. Hence, this qualitative study explored adolescents' perceptions on their patterns of use and factors influencing use, and perceptions and concerns from parents. Methods: Semi-structured interviews were conducted with adolescents (n = 36; 11 to 18 years) and their parents/caregivers (n = 28) in Singapore recruited to represent males and females across a range of ages from different socioeconomic groups. Prompts covered weekday and weekend use patterns, types of activities, perspectives on amount of use, parental control measures and concerns. Interviews were recorded and transcribed. Transcripts were coded and thematic analysis was carried out. Results: Smartphone was the most common mobile device owned and used by many of the adolescents, while only some used a tablet. Many adolescents and their parents felt that adolescents' MTSD use was high, frequent and ubiquitous, with frequent checking of device and multitasking during use. Reported influences of use included functional, personal and external influences. Some of the influences were irresistibility of mobile devices, lack of self-control, entertainment or relaxation value, and high use by peers, family and for schoolwork that contributed to high use, or school/parental control measures and lack of internet availability that limited use. Most adolescents were generally unconcerned about their use and perceived their usage as appropriate, while most parents expressed several concerns about their adolescents' use and perceived their usage as excessive. Conclusions: This study has provided rich insights into the patterns and influences of contemporary mobile device use by adolescents. Mobile device use has become an integral part of adolescents' daily routines, and was affected by several functional, personal and external influences which either facilitated or limited their use. There also seemed to be a strong inclination for adolescents to frequently check and use their mobile devices. There is an urgent need to understand the implications of these common adolescent behaviours to inform advice for wise mobile device use by adolescents

Tuftsin Promotes an Anti-Inflammatory Switch and Attenuates Symptoms in Experimental Autoimmune Encephalomyelitis

Multiple sclerosis (MS) is a demyelinating autoimmune disease mediated by infiltration of T cells into the central nervous system after compromise of the blood-brain barrier. We have previously shown that administration of tuftsin, a macrophage/microglial activator, dramatically improves the clinical course of experimental autoimmune encephalomyelitis (EAE), a well-established animal model for MS. Tuftsin administration correlates with upregulation of the immunosuppressive Helper-2 Tcell (Th2) cytokine transcription factor GATA-3. We now show that tuftsin-mediated microglial activation results in shifting microglia to an anti-inflammatory phenotype. Moreover, the T cell phenotype is shifted towards immunoprotection after exposure to tuftsin-treated activated microglia; specifically, downregulation of pro-inflammatory Th1 responses is triggered in conjunction with upregulation of Th2-specific responses and expansion of immunosuppressive regulatory T cells (Tregs). Finally, tuftsin-shifted T cells, delivered into animals via adoptive transfer, reverse the pathology observed in mice with established EAE. Taken together, our findings demonstrate that tuftsin decreases the proinflammatory environment of EAE and may represent a therapeutic opportunity for treatment of MS