A fast method for fuzzy neural modeling and refinement

In the identification of complex dynamic systems using fuzzy neural networks, one of the main issues is the curse of dimensionality, which makes it difficult to retain a large number of system inputs or to consider a large number of fuzzy sets. Moreover, due to the correlations, not all possible network inputs or regression vectors in the network are necessary and adding them simply increases the model complexity and deteriorates the network generalisation performance. In this paper, the problem is solved by first proposing a fast algorithm for selection of network terms, and then introducing a refinement procedure to tackle the correlation issue. Simulation results show the efficacy of the method.

The impact of adversity in childhood on outcomes in adulthood: research lessons and limitations

Summary: Current UK Government policy is concerned with the possible connections between childhood adversity, social exclusion and negative outcomes in adulthood. Understanding the impact of adverse childhood experiences on outcomes in adulthood is therefore key to informing effective policy and practice. In this article, the research on the impact of childhood adversity on outcomes in adulthood is reviewed in the broad categories of: mental health and social functioning; physical health; offending; service use; and economic impact. The literature on resilience that focuses on those who experience adversity, but do not have associated negative outcomes is also briefly considered. The strengths and limitations of the range of research methods used are then examined. Findings: Previous studies have tended to focus on specific forms of adversity, predominantly abuse and neglect, and either: specific populations and specific outcomes; specific populations and general outcomes; or general populations and specific outcomes. This means there may be incomplete understanding of the inputs (the range of adverse experiences in childhood), the processes (how these may affect people) and the outcomes (across domains in adulthood). Applications: It is concluded that it is important for social work researchers to engage in the current debate about how to prevent harmful childhood adversity and there is an important gap in the research for more interdisciplinary large-scale general population studies that consider the full range of childhood adversity and associated impacts across time and the possible processes involved.

Modelling the Geometry of the Repeat Unit Cell of Three-Dimensional Weave Architectures,

The three-dimensional (3D) weaving process offers the ability to tailor the mechanical properties via design of the weave architecture. One repeat of the 3D woven fabric is represented by the unit cell. The model accepts basic weaver and material manufacturer data as inputs in order to calculate the geometric characteristics of the 3D woven unit cell. The specific weave architecture manufactured and subsequently modelled had an angle interlock type binding configuration. The modelled result was shown to have a close approximation compared to the experimentally measured values and highlighted the importance of the representation of the binder tow path.

From PASS 1 to YES to AND logic: building parallel processing into molecular logic gates by sequential addition of receptors

The synthesis and photophysical characterization of a novel molecular logic gate 4, operating in water, is demonstrated based on the competition between. fluorescence and photoinduced electron transfer (PET). It is constructed according to a 'fluorophore-spacer-receptor(1)-spacer-receptor(2)' format where anthracene is the. fluorophore, receptor(1) is a tertiary amine and receptor(2) is a phenyliminodiacetate ligand. Using only protons and zinc cations as the chemical inputs and. fluorescence as the output, 4 is demonstrated to be both a two-input AND and INH logic gate. When 4 is examined in context to the YES logic gates 1 and 2, and the two-input AND logic gate 3 and three-input AND logic gate 5, each with one or more of the following receptors including a tertiary amine, phenyliminodiacetate or benzo-15-crown-5 ether, logic gate 4 is the missing link in the homologous series. Collectively, the molecular logic gates 1-5 corroborate the PET 'fluorophore-spacer-receptor' model using chemical inputs and a light-signal output and provide insight into controlling the. fluorescence quantum yield of future PET-based molecular logic gates.

delta C-13 and delta N-15 reveal significant differences in the coastal foodwebs of the seas surrounding Trinidad and Tobago

This study assessed nearshore, marine ecosystem function around Trinidad and Tobago (TT). The coastline of TT is highly complex, bordered by the Atlantic Ocean, the Caribbean Sea, the Gulf of Paria and the Columbus Channel, and subject to local terrestrial runoff and regional riverine inputs (e.g. the Orinoco and Amazon rivers). Coastal organisms can assimilate energy from allochthonous and autochthonous Sources, We assessed whether stable isotopes delta C-13 and delta N-15 Could be used to provide a rapid assessment of trophic interactions in primary consumers around the islands. Filter-feeding (bivalves and barnacles) and grazing organisms (gastropods and chitons) were collected from 40 marine sites during the wet season. The flesh of organisms was analysed for delta C-13 and delta N-15. Results indicate significant variation in primary consumers (by feeding guild and sampling zone). This variation was linked to different energy Sources being assimilated by consumers. Results suggest that offshore production is fuelling intertidal foodwebs; for example, a depleted delta C-13 signature in grazers from the Gulf of Paria, Columbus Channel and the Caribbean and Atlantic coastline of 9 Tobago indicates that carbon with an offshore origin (e.g. phytoplankton and dissolved organic matter) is more important than benthic or littoral algae (luring the wet season. Results also confirm findings from other studies indicating that much of the coastline is subject to Cultural eutrophication. This Study revealed that ecosystem function is spatially variable around the coastline of TT, This has clear implications for marine resource management, as a single management approach is unlikely to be successful at a national level.

Viscoelastic Material Models of Polypropylene for Thermoforming Applications

Polypropylene (PP), a semi-crystalline material, is typically solid phase thermoformed at temperatures associated with crystalline melting, generally in the 150° to 160°Celsius range. In this very narrow thermoforming window the mechanical properties of the material rapidly decline with increasing temperature and these large changes in properties make Polypropylene one of the more difficult materials to process by thermoforming. Measurement of the deformation behaviour of a material under processing conditions is particularly important for accurate numerical modelling of thermoforming processes. This paper presents the findings of a study into the physical behaviour of industrial thermoforming grades of Polypropylene. Practical tests were performed using custom built materials testing machines and thermoforming equipment at Queen′s University Belfast. Numerical simulations of these processes were constructed to replicate thermoforming conditions using industry standard Finite Element Analysis software, namely ABAQUS and custom built user material model subroutines. Several variant constitutive models were used to represent the behaviour of the Polypropylene materials during processing. This included a range of phenomenological, rheological and blended constitutive models. The paper discusses approaches to modelling industrial plug-assisted thermoforming operations using Finite Element Analysis techniques and the range of material models constructed and investigated. It directly compares practical results to numerical predictions. The paper culminates discussing the learning points from using Finite Element Methods to simulate the plug-assisted thermoforming of Polypropylene, which presents complex contact, thermal, friction and material modelling challenges. The paper makes recommendations as to the relative importance of these inputs in general terms with regard to correlating to experimentally gathered data. The paper also presents recommendations as to the approaches to be taken to secure simulation predictions of improved accuracy.

Real-time error detection but not error correction drives automatic visuomotor adaptation

We investigated the role of visual feedback of task performance in visuomotor adaptation. Participants produced novel two degrees of freedom movements (elbow flexion-extension, forearm pronation-supination) to move a cursor towards visual targets. Following trials with no rotation, participants were exposed to a 60A degrees visuomotor rotation, before returning to the non-rotated condition. A colour cue on each trial permitted identification of the rotated/non-rotated contexts. Participants could not see their arm but received continuous and concurrent visual feedback (CF) of a cursor representing limb position or post-trial visual feedback (PF) representing the movement trajectory. Separate groups of participants who received CF were instructed that online modifications of their movements either were, or were not, permissible as a means of improving performance. Feedforward-mediated performance improvements occurred for both CF and PF groups in the rotated environment. Furthermore, for CF participants this adaptation occurred regardless of whether feedback modifications of motor commands were permissible. Upon re-exposure to the non-rotated environment participants in the CF, but not PF, groups exhibited post-training aftereffects, manifested as greater angular deviations from a straight initial trajectory, with respect to the pre-rotation trials. Accordingly, the nature of the performance improvements that occurred was dependent upon the timing of the visual feedback of task performance. Continuous visual feedback of task performance during task execution appears critical in realising automatic visuomotor adaptation through a recalibration of the visuomotor mapping that transforms visual inputs into appropriate motor commands.

hVps34 is a nutrient-regulated lipid kinase required for activation of p70 S6 kinase

Mammalian cells respond to nutrient deprivation by inhibiting energy consuming processes, such as proliferation and protein synthesis, and by stimulating catabolic processes, such as autophagy. p70 S6 kinase (S6K1) plays a central role during nutritional regulation of translation. S6K1 is activated by growth factors such as insulin, and by mammalian target of rapamycin (mTOR), which is itself regulated by amino acids. The Class IA phosphatidylinositol (PI) 3-kinase plays a well recognized role in the regulation of S6K1. We now present evidence that the Class III PI 3-kinase, hVps34, also regulates S6K1, and is a critical component of the nutrient sensing apparatus. Overexpression of hVps34 or the associated hVps15 kinase activates S6K1, and insulin stimulation of S6K1 is blocked by microinjection of inhibitory anti-hVps34 antibodies, overexpression of a FYVE domain construct that sequesters the hVps34 product PI(3) P, or small interfering RNA-mediated knock-down of hVps34. hVps34 is not part of the insulin input to S6K1, as it is not stimulated by insulin, and inhibition of hVps34 has no effect on phosphorylation of Akt or TSC2 in insulin-stimulated cells. However, hVps34 is inhibited by amino acid or glucose starvation, suggesting that it lies on the nutrient-regulated pathway to S6K1. Consistent with this, hVps34 is also inhibited by activation of the AMP-activated kinase, which inhibits mTOR/S6K1 in glucose-starved cells. hVps34 appears to lie upstream of mTOR, as small interfering RNA knock- down of hVps34 inhibits the phosphorylation of another mTOR substrate, eIF4E-binding protein-1 (4EBP1). Our data suggest that hVps34 is a nutrient-regulated lipid kinase that integrates amino acid and glucose inputs to mTOR and S6K1.

Can China’s Growth be Sustained? A Productivity Perspective

China’s gradual approach to economic transition has resulted in sustained high growth. However, in recent years Chinese economists have increasingly referred to the growth pattern as “extensive,” generated mainly through the expansion of inputs. Our investigation of the Chinese economy during the reform period finds that reform measures often resulted in one-time level effects on total factor productivity (TFP). China now needs to adjust its reform program toward sustained increases in productivity. Market and ownership reforms, and open door policies have improved the conditions under which Chinese firms operate, but further institutional reforms are required to consolidate China’s move to a full-fledged market economy.

An efficient feature selection method for mobile devices with application to activity recognition

This paper presents a feature selection method for data classification, which combines a model-based variable selection technique and a fast two-stage subset selection algorithm. The relationship between a specified (and complete) set of candidate features and the class label is modelled using a non-linear full regression model which is linear-in-the-parameters. The performance of a sub-model measured by the sum of the squared-errors (SSE) is used to score the informativeness of the subset of features involved in the sub-model. The two-stage subset selection algorithm approaches a solution sub-model with the SSE being locally minimized. The features involved in the solution sub-model are selected as inputs to support vector machines (SVMs) for classification. The memory requirement of this algorithm is independent of the number of training patterns. This property makes this method suitable for applications executed in mobile devices where physical RAM memory is very limited. An application was developed for activity recognition, which implements the proposed feature selection algorithm and an SVM training procedure. Experiments are carried out with the application running on a PDA for human activity recognition using accelerometer data. A comparison with an information gain based feature selection method demonstrates the effectiveness and efficiency of the proposed algorithm.

Experimental Investigation of Stretch Blow Molding, Part 2: Analysis of Process Variables, Blowing Kinematics, and Bottle Properties

The work presented in this paper takes advantage of newly developed instrumentation suitable for in process monitoring of an industrial stretch blow molding machine. The instrumentation provides blowing pressure and stretch rod force histories along with the kinematics of polymer contact with the mould wall. A Design of Experiments pattern was used to qualitatively relate machine inputs with these process parameters and the thickness distribution of stretch blow molded PET (polyethylene terephtalate) bottles. Material slippage at the mold wall and thickness distribution is also discussed in relation to machine inputs. The key process indicators defined have great potential for use in a closed loop process control system and for validation of process simulations.

Agricultural intensification and biodiversity partitioning in European landscapes comparing plants, carabids, and birds

Effects of agricultural intensification (AI) on biodiversity are often assessed on the plot scale, although processes determining diversity also operate on larger spatial scales. Here, we analyzed the diversity of vascular plants, carabid beetles, and birds in agricultural landscapes in cereal crop fields at the field (n = 1350), farm (n = 270), and European-region (n = 9) scale. We partitioned diversity into its additive components alpha, beta, and gamma, and assessed the relative contribution of beta diversity to total species richness at each spatial scale. AI was determined using pesticide and fertilizer inputs, as well as tillage operations and categorized into low, medium, and high levels. As AI was not significantly related to landscape complexity, we could disentangle potential AI effects on local vs. landscape community homogenization. AI negatively affected the species richness of plants and birds, but not carabid beetles, at all spatial scales. Hence, local AI was closely correlated to beta diversity on larger scales up to the farm and region level, and thereby was an indicator of farm-and region-wide biodiversity losses. At the scale of farms (12.83-20.52%) and regions (68.34-80.18%), beta diversity accounted for the major part of the total species richness for all three taxa, indicating great dissimilarity in environmental conditions on larger spatial scales. For plants, relative importance of alpha diversity decreased with AI, while relative importance of beta diversity on the farm scale increased with AI for carabids and birds. Hence, and in contrast to our expectations, AI does not necessarily homogenize local communities, presumably due to the heterogeneity of farming practices. In conclusion, a more detailed understanding of AI effects on diversity patterns of various taxa and at multiple spatial scales would contribute to more efficient agri-environmental schemes in agroecosystems.

Persistent negative effects of pesticides on biodiversity and biological control potential on European farmland

During the last 50 years, agricultural intensification has caused many wild plant and animal species to go extinct regionally or nationally and has profoundly changed the functioning of agro-ecosystems. Agricultural intensification has many components, such as loss of landscape elements, enlarged farm and field sizes and larger inputs of fertilizer and pesticides. However, very little is known about the relative contribution of these variables to the large-scale negative effects on biodiversity. In this study, we disentangled the impacts of various components of agricultural intensification on species diversity of wild plants, carabids and ground-nesting farmland birds and on the biological control of aphids.

Luminescent Photoinduced Electron Transfer (PET) Molecules for Sensing and Logic Operations

Chemical species can serve as inputs to supramolecular devices so that a luminescence output is created in a conditional manner. Conditionality is built into these devices by employing the classical photochemical process of photoinduced electron transfer (PET) to compete with luminescence emission. The response of these devices in the analogue regime leads to sensors that can operate in nanometric, micrometric, and millimetric spaces. Some of these devices serve in membrane science, cell physiology, and medical diagnostics. The response in the digital regime leads to Boolean logic gates. Some of these find application in improving aspects of medical diagnostics and in identifying small objects in large populations.

Molecular Logic Gates and Luminescent Sensors Based on Photoinduced Electron Transfer

The competition between Photoinduced electron transfer (PET) and other de-excitation pathways such as fluorescence and phosphorescence can be controlled within designed molecular structures. Depending on the particular design, the resulting optical output is thus a function of various inputs such as ion concentration and excitation light dose. Once digitized into binary code, these input-output patterns can be interpreted according to Boolean logic. The single-input logic types of YES and NOT cover simple sensors and the double- (or higher-) input logic types represent other gates such as AND and OR. The logic-based arithmetic processors such as half-adders and half-subtractors are also featured. Naturally, a principal application of the more complex gates is in multi-sensing contexts.