How the mollusc got its scales: Convergent evolution of the molluscan scleritome

Radiation of dramatically disparate forms among the phylum Mollusca remains a key question in metazoan evolution, and requires careful evaluation of homology of hard parts throughout the deep fossil record. Enigmatic early Cambrian taxa such as Halkieria and Wiwaxia (in the clade Halwaxiida) have been proposed to represent stem-group aculiferan molluscs (Caudofoveata+Solenogastres+Polyplacophora), as complex scleritomes were considered to be unique to aculiferans among extant molluscs. The 'scaly-foot gastropod' (Neomphalina: Peltospiridae) from hydrothermal vents of the Indian Ocean, however, also carries dermal sclerites and thus challenges this inferred homology. Despite superficial similarities to various mollusc sclerites, the scaly-foot gastropod sclerites are secreted in layers covering outpockets of epithelium and are largely proteinaceous, while chiton (Polyplacophora: Chitonida) sclerites are secreted to fill an invaginated cuticular chamber and are largely calcareous. Marked differences in the underlying epithelium of the scaly-foot gastropod sclerites and operculum suggest that the sclerites do not originate from multiplication of the operculum. This convergence in different classes highlights the ability of molluscs to adapt mineralized dermal structures, as supported by the extensive early fossil record of molluscs with scleritomes. Sclerites of halwaxiids are morphologically variable, undermining the assumed affinity of specific taxa with chitons, or the larger putative clade Aculifera. Comparisons with independently derived similar structures in living molluscs are essential for determining homology among fossils and their position with respect to the enigmatic evolution of molluscan shell forms in deep time.

High Strength Thermoplastic Bonding for Multi-channel, Multi-layer Lab-on-Chip Devices for Ocean and Environmental applications

A solvent-vapour thermoplastic bonding process is reported which provides high strength bonding of PMMA over a large area for multi-channel and multi-layer microfluidic devices with shallow high resolution channel features. The bond process utilises a low temperature vacuum thermal fusion step with prior exposure of the substrate to chloroform (CHCl3) vapour to reduce bond temperature to below the PMMA glass transition temperature. Peak tensile and shear bond strengths greater than 3 MPa were achieved for a typical channel depth reduction of 25 µm. The device-equivalent bond performance was evaluated for multiple layers and high resolution channel features using double-side and single-side exposure of the bonding pieces. A single-sided exposure process was achieved which is suited to multi-layer bonding with channel alignment at the expense of greater depth loss and a reduction in peak bond strength. However, leak and burst tests demonstrate bond integrity up to at least 10 bar channel pressure over the full substrate area of 100 mm x 100 mm. The inclusion of metal tracks within the bond resulted in no loss of performance. The vertical wall integrity between channels was found to be compromised by solvent permeation for wall thicknesses of 100 µm which has implications for high resolution serpentine structures. Bond strength is reduced considerably for multi-layer patterned substrates where features on each layer are not aligned, despite the presence of an intermediate blank substrate. Overall a high performance bond process has been developed that has the potential to meet the stringent specifications for lab-on-chip deployment in harsh environmental conditions for applications such as deep ocean profiling.

Material Identification of Loose Particles in Sealed Electronic Devices Using PCA and SVM

The existence of loose particles left inside the sealed electronic devices is one of the main factors affecting the reliability of the whole system. It is important to identify the particle material for analyzing their source. The conventional material identification algorithms mainly rely on time, frequency and wavelet domain features. However, these features are usually overlapped and redundant, resulting in unsatisfactory material identification accuracy. The main objective of this paper is to improve the accuracy of material identification. First, the principal component analysis (PCA) is employed to reselect the nine features extracted from time and frequency domains, leading to six less correlated principal components. And then the reselected principal components are used for material identification using a support vector machine (SVM). Finally, the experimental results show that this new method can effectively distinguish the type of materials including wire, aluminum and tin particles.

Long-Term Economic Model for Allocation of FACTS Devices in Restructured Power System Integrated Wind Generation

This study proposes an approach to optimally allocate multiple types of flexible AC transmission system (FACTS) devices in market-based power systems with wind generation. The main objective is to maximise profit by minimising device investment cost, and the system's operating cost considering both normal conditions and possible contingencies. The proposed method accurately evaluates the long-term costs and benefits gained by FACTS devices (FDs) installation to solve a large-scale optimisation problem. The objective implies maximising social welfare as well as minimising compensations paid for generation re-scheduling and load shedding. Many technical operation constraints and uncertainties are included in problem formulation. The overall problem is solved using both particle swarm optimisations for attaining optimal FDs allocation as main problem and optimal power flow as sub-optimisation problem. The effectiveness of the proposed approach is demonstrated on modified IEEE 14-bus test system and IEEE 118-bus test system.

Validity of model devices used to assess canine temperament in behavioral tests

Temperament tests are widely accepted as instruments for profiling behavioral variability in dogs, and they are applied in numerous areas of investigation (e.g. suitability for adoption or for breeding). During testing, to elicit a dog's reaction toward novel stimuli and predict its behavior in everyday life, model devices such as a child-like doll, or a fake dog, are often employed. However, the reliability of these devices to accurately stimulate dogs' reactions to children or dogs, is unknown and perhaps overestimated. This may be a particular concern in the case of aggressive behavior toward humans, a significant public health issue. The aim of this study was to: (1) evaluate the correlation between dogs' reactions to these devices, and owners' reports of their dog's aggression history (using the C-BARQ ??); (2) compare reactions toward the devices of dogs with and without histories of aggression. Subjects were selected among those visiting for behavioral consultation at the Veterinary Hospital of the University of Pennsylvania, and previously categorized as aggressive toward unfamiliar children, conspecifics, or as non-aggressive dogs (control). The test consisted of different components: an unfamiliar female tester approaching the dog; the presentation of a child-like doll, an ambiguous object, and a fake plastic dog. All tests were videotaped and durations of behaviors were later analyzed on the basis of a specified ethogram. Dogs' reactions were compared to C-BARQ scores, and interesting correlations emerged for 'dog-directed aggression/fear' (R = 0.48, P = 0.004), and 'stranger-directed aggression' (R = 0.58, P <0.001) factors. Dogs differed in their reactions toward the devices: the child-like doll and the fake dog elicited more social behaviors than the ambiguous object used as a control stimulus. Issues concerning the reliability of these tools to assess canine temperament are discussed. ?? 2012 Elsevier B.V. All rights reserved.

Spatial variation in adult sex ratio across multiple scales in the invasive golden apple snail, Pomacea canaliculata

Adult sex ratio (ASR) has critical effects on behavior and life history and has implications for population demography, including the invasiveness of introduced species. ASR exhibits immense variation in nature, yet the scale dependence of this variation is rarely analyzed. In this study, using the generalized multilevel models, we investigated the variation in ASR across multiple nested spatial scales and analyzed the underlying causes for an invasive species, the golden apple snail Pomacea canaliculata. We partitioned the variance in ASR to describe the variations at different scales and then included the explanatory variables at the individual and group levels to analyze the potential causes driving the variation in ASR. We firstly determined there is a significant female-biased ASR for this species when accounting for the spatial and temporal autocorrelations of sampling. We found that, counter to nearly equal distributed variation at plot, habitat and region levels, ASR showed little variation at the town level. Temperature and precipitation at the region level were significantly positively associated with ASR, whereas the individual weight, the density characteristic, and sampling time were not significant factors influencing ASR. Our study suggests that offspring sex ratio of this species may shape the general pattern of ASR in the population level while the environmental variables at the region level translate the unbiased offspring sex ratio to the female-biased ASR. Future research should consider the implications of climate warming on the female-biased ASR of this invasive species and thus on invasion pattern.

A closer look at Carver and White's BIS/BAS scales: Factor analysis and age group differences

The Behavioural Inhibition and Behavioural Activation System (BIS/BAS) scales were developed by Carver and White (1994) and comprise four scales which measure individual differences in personality (Gray 1982, 1991). More recent modifications, namely the five-factor model derived from Gray and McNaughton's (2000) revised Reward Sensitivity Theory (RST) suggests that Anxiety and Fear are separable components of inhibition. This study employed exploratory and confirmatory factor analyses on the scales in order to test whether the four or five-factor model was the better fit in a sample of 994 participants aged 11–30 years. Consistent with RST, superior model fit was shown for the five-factor model with all variables correlated. Significant age effects were observed for BIS Fear and BIS Anxiety, with scores peaking in middle and late adolescence respectively. The BAS subscales showed differential effects of age group. Significantly increasing scores from early to mid and from mid to late adolescence were found for Drive, but the effect of age on Fun Seeking and Reward Responsiveness was not significant.

Abstract: Psychometric properties of two self-report clinical competence scales for nursing students.

Abstract: Psychometric properties of two self-report clinical competence scales for nursing students.
Background: It is important to assess the clinical competence of nursing students to gauge their professional development and educational needs. This can be measured by self-assessment tools. Anema and McCoy (2010) contended that the currently available measures need further psychometric testing.
Aim: To test the psychometric properties of Nursing Competencies Questionnaire (NCQ) and Self-Efficacy in Clinical Performance (SECP) clinical competence scales.

Method: A non-randomly selected sample of n=248 2nd year nursing students completed NCQ, SECP and demographic questionnaires (June and September 2013). Mokken Scaling Analysis (MSA) was used to test the structural validity and scale properties, convergent and discriminant validity and reliability were subsequently tested.

Results: The NCQ provided evidence of a unidimensional scale which had strong scale scalability coefficients Hs =0.581; but limited evidence of item rankability HT =0.367. MSA undertaken with the SECP scale identified two potential unidimensional scales the SECP28 and SECP7, each with adequate evidence of good/reasonable scalablity psychometric properties as a summed scale but no/very limited evidence of scale rankability (SECP28: Hs = 0.55, HT=0.211; SECP7: Hs = 0.61, HT=0.049). Analysis of between cohort differences and NCQ/ SECP scale scores produced evidence of convergent and discriminant validity and good internal reliability: NCQ α = 0.93, SECP28 α = 0.96, and SECP7 α=0.89.

Discussion: The NCQ was verified to have evidence of reliability and validity; however, as the SECP findings are new, and the sample small, with reference to Straat and colleagues (2014), the SECP results should be interpreted with caution and verified on a second sample.

Conclusions: Measurement of perceived self-competence could inform the development of nursing competence and could start early in a nursing programme. Further testing of the NCQ and SECP scales with larger samples and from different years is indicated.


References:
Anema, M., G and McCoy, JK. (2010) Competency-Based Nursing Education: Guide to Achieving Outstanding Learner Outcomes. New York: Springer.
Straat, JH., van der Ark, LA and Sijtsma, K. (2014) Minimum Sample Size Requirements for Mokken Scale Analysis Educational and Psychological Measurement 74 (5), 809-822.

Heterogeneous error-resilient scheme for spectral analysis in ultra-low power wearable electrocardiogram devices

Wearable devices performing advanced bio-signal analysis algorithms are aimed to foster a revolution in healthcare provision of chronic cardiac diseases. In this context, energy efficiency is of paramount importance, as long-term monitoring must be ensured while relying on a tiny power source. Operating at a scaled supply voltage, just above the threshold voltage, effectively helps in saving substantial energy, but it makes circuits, and especially memories, more prone to errors, threatening the correct execution of algorithms. The use of error detection and correction codes may help to protect the entire memory content, however it incurs in large area and energy overheads which may not be compatible with the tight energy budgets of wearable systems. To cope with this challenge, in this paper we propose to limit the overhead of traditional schemes by selectively detecting and correcting errors only in data highly impacting the end-to-end quality of service of ultra-low power wearable electrocardiogram (ECG) devices. This partition adopts the protection of either significant words or significant bits of each data element, according to the application characteristics (statistical properties of the data in the application buffers), and its impact in determining the output. The proposed heterogeneous error protection scheme in real ECG signals allows substantial energy savings (11% in wearable devices) compared to state-of-the-art approaches, like ECC, in which the whole memory is protected against errors. At the same time, it also results in negligible output quality degradation in the evaluated power spectrum analysis application of ECG signals.