Suzhi development: Indigenous approaches to enhancing the quality of human resources

Purpose- This paper aims to examine the Chinese indigenous concept of suzhi ((ProQuest: Non US-ASCII text omitted)) by analyzing its historical evolution and its contemporary implications for human resource management (HRM) research and practice at the national and organizational levels.Design/methodology/approach- An integrated review of literatures in sinology, political science, anthropology and sociology concerned with suzhi-related research, combined with recent incidents associated with suzhi.Findings-Suzhi is an indigenous concept embedded in the centuries-long historical context of China.Suzhi development has been focused on three key dimensions, moral, physical and mental, as a way of building quality employees and citizens. Yet developing and quantifying the moral aspects ofsuzhi is more challenging than measuring its physical and mental dimensions. Linkingsuzhi development to human capital theory enriches the understanding of this indigenous concept at both organizational and national levels.Research limitations/implications- By analyzing a three-dimensionalsuzhi composite, the article offers an example of howsuzhi may be linked to human capital theory and identifies directions for future research.Originality/value- By analyzingsuzhi at organizational and national levels for HRM purposes, this article broadens thesuzhi literature from its place in the political sciences and social anthropology to encompass a theoretical analysis in HRM and development for the benefit of organizations and the society.

Uncertainty handling using neural network-based prediction intervals for electrical load forecasting

The complexity and level of uncertainty present in operation of power systems have significantly grown due to penetration of renewable resources. These complexities warrant the need for advanced methods for load forecasting and quantifying uncertainties associated with forecasts. The objective of this study is to develop a framework for probabilistic forecasting of electricity load demands. The proposed probabilistic framework allows the analyst to construct PIs (prediction intervals) for uncertainty quantification. A newly introduced method, called LUBE (lower upper bound estimation), is applied and extended to develop PIs using NN (neural network) models. The primary problem for construction of intervals is firstly formulated as a constrained single-objective problem. The sharpness of PIs is treated as the key objective and their calibration is considered as the constraint. PSO (particle swarm optimization) enhanced by the mutation operator is then used to optimally tune NN parameters subject to constraints set on the quality of PIs. Historical load datasets from Singapore, Ottawa (Canada) and Texas (USA) are used to examine performance of the proposed PSO-based LUBE method. According to obtained results, the proposed probabilistic forecasting method generates well-calibrated and informative PIs. Furthermore, comparative results demonstrate that the proposed PI construction method greatly outperforms three widely used benchmark methods. © 2014 Elsevier Ltd.

Winter foraging site fidelity of king penguins breeding at the Falkland Islands

Foraging site fidelity has profound consequences for individual fitness, population processes and the effectiveness of species conservation measures. Accordingly, quantifying site fidelity has become increasingly important in animal movement and habitat selection studies. To assess foraging site fidelity in king penguins (Aptenodytes patagonicus) breeding at the Falkland Islands (51.48°S, 57.83°W), we measured overlap in time spent in foraging areas (at a 0.1° × 0.1° grid resolution) between successive foraging trips and foraging route consistency during the crèche period. In total, 30 complete foraging trips from seven king penguins were recorded between April and October 2010. King penguins predominantly foraged on the highly productive Patagonian slope, to the north of the Falkland Islands [median foraging trip distance 213 km (SD = 215 km) and duration 12.8 days (SD = 14.7 days)]. Overlap in time spent in an area on consecutive foraging trips ranged between 2 and 73 % (mean 27 %, SD = 22 %). Bearing during the outbound portion of foraging trips was typically highly repeatable for individual birds, but foraging trip duration and distance were not. Travel during the outbound phase of foraging trips was consistent with the direction of the northward-flowing Falkland Current that may act as a directional cue or facilitate rapid transit to foraging areas. Flexibility in foraging trip distances and durations may be a response to changes in resource availability and changes in the energetic requirements of adults and chicks over an extended breeding cycle.

Automated quantification of neurite outgrowth orientation distributions on patterned surfaces

Objective. We have developed an image analysis methodology for quantifying the anisotropy of neuronal projections on patterned substrates. Approach. Our method is based on the fitting of smoothing splines to the digital traces produced using a non-maximum suppression technique. This enables precise estimates of the local tangents uniformly along the neurite length, and leads to unbiased orientation distributions suitable for objectively assessing the anisotropy induced by tailored surfaces. Main results. In our application, we demonstrate that carbon nanotubes arrayed in parallel bundles over gold surfaces induce a considerable neurite anisotropy; a result which is relevant for regenerative medicine. Significance. Our pipeline is generally applicable to the study of fibrous materials on 2D surfaces and should also find applications in the study of DNA, microtubules, and other polymeric materials.

Habitat classification of temperate marine macroalgal communities using bathymetric LiDAR

Here, we evaluated the potential of using bathymetric Light Detection and Ranging (LiDAR) to characterise shallow water (<30 m) benthic habitats of high energy subtidal coastal environments. Habitat classification, quantifying benthic substrata and macroalgal communities, was achieved in this study with the application of LiDAR and underwater video groundtruth data using automated classification techniques. Bathymetry and reflectance datasets were used to produce secondary terrain derivative surfaces (e.g., rugosity, aspect) that were assumed to influence benthic patterns observed. An automated decision tree classification approach using the Quick Unbiased Efficient Statistical Tree (QUEST) was applied to produce substrata, biological and canopy structure habitat maps of the study area. Error assessment indicated that habitat maps produced were primarily accurate (>70%), with varying results for the classification of individual habitat classes; for instance, producer accuracy for mixed brown algae and sediment substrata, was 74% and 93%, respectively. LiDAR was also successful for differentiating canopy structure of macroalgae communities (i.e., canopy structure classification), such as canopy forming kelp versus erect fine branching algae. In conclusion, habitat characterisation using bathymetric LiDAR provides a unique potential to collect baseline information about biological assemblages and, hence, potential reef connectivity over large areas beyond the range of direct observation. This research contributes a new perspective for assessing the structure of subtidal coastal ecosystems, providing a novel tool for the research and management of such highly dynamic marine environments. © 2014 by the authors; licensee MDPI, Basel, Switzerland.

Confocal laser scanning microscopy elucidation of the micromorphology of the leaf cuticle and analysis of its chemical composition

Electron microscopy techniques such as transmission electron microscopy (TEM) and scanning electron microscopy (SEM) have been invaluable tools for the study of the micromorphology of plant cuticles. However, for electron microscopy, the preparation techniques required may invariably introduce artefacts in cuticle preservation. Further, there are a limited number of methods available for quantifying the image data obtained through electron microscopy. Therefore, in this study, optical microscopy techniques were coupled with staining procedures and, along with SEM were used to qualitatively and quantitatively assess the ultrastructure of plant leaf cuticles. Leaf cryosections of Triticum aestivum (wheat), Zea mays (maize), and Lupinus angustifolius (lupin) were stained with either fat-soluble azo stain Sudan IV or fluorescent, diarylmethane Auramine O and were observed under confocal laser scanning microscope (CLSM). For all the plant species tested, the cuticle on the leaf surfaces could be clearly resolved in many cases into cuticular proper (CP), external cuticular layer (ECL), and internal cuticular layer (ICL). Novel image data analysis procedures for quantifying the epicuticular wax micromorphology were developed, and epicuticular waxes of L. angustifolius were described here for the first time. Together, application of a multifaceted approach involving the use of a range of techniques to study the plant cuticle has led to a better understanding of cuticular structure and provides new insights into leaf surface architecture.

An overview of new progresses in understanding pipeline corrosion

An approach to achieving the ambitious goal of cost effectively extending the safe operation life of energy pipeline to 100 years is the application of health monitoring and life prediction tools that are able to provide both long-term remnant pipeline life prediction and in-situ pipeline condition monitoring. A critical step is the enhancement of technological capabilities that are required for understanding and quantifying the effects of key factors influencing buried steel pipeline corrosion and environmentally assisted materials degradation, and the development of condition monitoring technologies that are able to provide in-situ monitoring and site-specific warning of pipeline damage. This paper provides an overview of our current research aimed at developing new sensors and electrochemical cells for monitoring, categorising and quantifying the level and nature of external pipeline and coating damages under the combined effects of various inter-related variables and processes such as localised corrosion, coating cracking and disbondment, cathodic shielding, transit loss of cathodic protection.

Experimental foot-and-mouth disease virus infection in white tailed deer

White tailed deer (Odocoileus virginianus) were inoculated with foot-and-mouth disease virus (FMDV) O UKG 11/2001 and monitored for the development of clinical signs, histopathological changes and levels of virus replication. All FMDV-infected deer developed clinical signs starting at 2 days post inoculation and characterized by an increase in body temperature, increased salivation and lesions in the mouth and on the feet. Virus spread to various tissues was determined by quantifying the amount of FMDV RNA using quantitative reverse transcriptase polymerase chain reaction. Virus or viral antigen was also detected in tissues using traditional isolation techniques, enzyme linked immunosorbent assay and immunohistochemistry. Deer-to-cattle transmission of the virus was observed in this experimental setting; however, inoculated deer were not found to become carriers of FMDV.

An integrative framework for the appraisal of coloration in nature

The world in color presents a dazzling dimension of phenotypic variation. Biological interest in this variation has burgeoned, due to both increased means for quantifying spectral information and heightened appreciation for how animals view the world differently than humans. Effective study of color traits is challenged by how to best quantify visual perception in nonhuman species. This requires consideration of at least visual physiology but ultimately also the neural processes underlying perception. Our knowledge of color perception is founded largely on the principles gained from human psychophysics that have proven generalizable based on comparative studies in select animal models. Appreciation of these principles, their empirical foundation, and the reasonable limits to their applicability is crucial to reaching informed conclusions in color research. In this article, we seek a common intellectual basis for the study of color in nature. We first discuss the key perceptual principles, namely, retinal photoreception, sensory channels, opponent processing, color constancy, and receptor noise. We then draw on this basis to inform an analytical framework driven by the research question in relation to identifiable viewers and visual tasks of interest. Consideration of the limits to perceptual inference guides two primary decisions: first, whether a sensory-based approach is necessary and justified and, second, whether the visual task refers to perceptual distance or discriminability. We outline informed approaches in each situation and discuss key challenges for future progress, focusing particularly on how animals perceive color. Given that animal behavior serves as both the basic unit of psychophysics and the ultimate driver of color ecology/evolution, behavioral data are critical to reconciling knowledge across the schools of color research.

Analysis of phasic and tonic electromyographic signal characteristics: electromyographic synthesis and comparison of novel morphological and linear-envelope approaches

The pattern of tonic and phasic components in an EMG signal reflects the underlying behaviour of the central nervous system (CNS) in controlling the musculature. One avenue for gaining a better understanding of this behaviour is to seek a quantitative characterisation of these phasic and tonic components. We propose that these signal characteristics can range between unvarying, tonic and intermittent, phasic activation through a continuum of EMG amplitude modulation. In this paper, we present two new algorithms for quantifying amplitude modulation: a linear-envelope approach, and a mathematical morphology approach. In addition we present an algorithm for synthesising EMG signals with known amplitude modulation. The efficacy of the synthesis algorithm is demonstrated using real EMG data. We present an evaluation and comparison of the two algorithms for quantifying amplitude modulation based on synthetic data generated by the proposed synthesis algorithm. The results demonstrate that the EMG synthesis parameters represent 91.9% and 96.2% of the variance of linear-envelopes extracted from lumbo-pelvic muscle EMG signals collected from subjects performing a repetitive-movement task. This depended, however, on the muscle and movement-speed considered (F=4.02, p<0.001). Coefficients of determination between input and output amplitude modulation variables were used to quantify the accuracy of the linear-envelope and morphological signal processing algorithms. The linear-envelope algorithm exhibited higher coefficients of determination than the most accurate morphological approach (and hence greater accuracy, T=8.16, p<0.001). Similarly, the standard deviation of the coefficients of determination was 1.691 times smaller (p<0.001). This signal processing algorithm represents a novel tool for the quantification of amplitude modulation in continuous EMG signals and can be used in the study of CNS motor control of the musculature in repetitive-movement tasks.

Tough decisions: Reproductive timing and output vary with individuals' physiology, behavior and past success in a social opportunistic breeder

This article is part of a Special Issue SBN 2014. Photoperiod and the hormonal response it triggers are key determinants of reproductive timing in birds. However, other cues and physiological traits may permit flexibility in the timing of breeding and perhaps facilitate adaptation to global change. Opportunistic breeders are excellent models to study the adaptive significance of this flexibility, especially at the individual level. Here, we sought to quantify whether particular male physiological and behavioral traits were linked to reproductive timing and output in wild-derived zebra finches. We repeatedly assessed male stress-induced corticosterone levels (CORT), basal metabolic rate (BMR), and activity before releasing them into outdoor aviaries and quantifying each pair's breeding timing, investment, and output over a seven-month period. Despite unlimited access to food and water, the colony breeding activity occurred in waves, probably due to interpair social stimulations. Pairs adjusted their inter-clutch interval and clutch size to social and temperature cues, respectively, but only after successful breeding attempts, suggesting a facultative response to external cues. When these effects were controlled for statistically or experimentally, breeding intervals were repeatable within individuals across reproductive attempts. In addition, males' first laying date and total offspring production varied with complex interactions between pre-breeding CORT, BMR and activity levels. These results suggest that no one trait is under selection but that, instead, correlational selection acts on hormone levels, metabolism, and behavior. Together our results suggest that studying inter-individual variation in breeding strategy and their multiple physiological and behavioral underpinnings may greatly improve our understanding of the mechanisms underlying the evolution of breeding decisions.

Utility of biological sensor tags in animal conservation

Electronic tags (both biotelemetry and biologging platforms) have informed conservation and resource management policy and practice by providing vital information on the spatial ecology of animals and their environments. However, the extent of the contribution of biological sensors (within electronic tags) that measure an animal's state (e.g., heart rate, body temperature, and details of locomotion and energetics) is less clear. A literature review revealed that, despite a growing number of commercially available state sensor tags and enormous application potential for such devices in animal biology, there are relatively few examples of their application to conservation. Existing applications fell under 4 main themes: quantifying disturbance (e.g., ecotourism, vehicular and aircraft traffic), examining the effects of environmental change (e.g., climate change), understanding the consequences of habitat use and selection, and estimating energy expenditure. We also identified several other ways in which sensor tags could benefit conservation, such as determining the potential efficacy of management interventions. With increasing sensor diversity of commercially available platforms, less invasive attachment techniques, smaller device sizes, and more researchers embracing such technology, we suggest that biological sensor tags be considered a part of the necessary toolbox for conservation. This approach can measure (in real time) the state of free-ranging animals and thus provide managers with objective, timely, relevant, and accurate data to inform policy and decision making.

Ocular exposure to UV-B in sunlight: the Melbourne Visual Impairment Project model

Quantification of ocular exposure to ultraviolet-B radiation (UV-B) has become an important public health issue, with reports that the ozone layer is being depleted worldwide. Ocular exposure to UV-B is determined by ambient UV-B levels, the duration of outdoor exposure, the proportion of ambient UV-B that reaches the eye, and the use of ocular protection. We have developed a simplified model for quantifying lifetime ocular UV-B exposure that can be used in large epidemiological surveys. Exposure to UV-B is assessed and quantified using a model based on personal exposure over the six summer months. Data available for a population-based sample of 1150 people in the age range 40-98 years revealed a distribution in average annual lifetime ocular UV-B exposure similar to that reported in a previous study on which this model is based, and also demonstrate that people can recall lifetime personal behaviour related to ocular protection. It takes 12 minutes on average to collect these data. This model can be employed by researchers worldwide for uniform assessment of ocular UV-B exposure.

Prediction interval-based control of nonlinear systems using neural networks

Prediction interval (PI) is a promising tool for quantifying uncertainties associated with point predictions. Despite its informativeness, the design and deployment of PI-based controller for complex systems is very rare. As a pioneering work, this paper proposes a framework for design and implementation of PI-based controller (PIC) for nonlinear systems. Neural network (NN)-based inverse model within internal model control structure is used to develop the PIC. Firstly, a PI-based model is developed to construct PIs for the system output. This model is then used as an online estimator for PIs. The PIs from this model are fed to the NN inverse model along with other traditional inputs to generate the control signal. The performance of the proposed PIC is examined for two case studies. This includes a nonlinear batch polymerization reactor and a numerical nonlinear plant. Simulation results demonstrated that the proposed PIC tracking performance is better than the traditional NN-based controller.

Structural health monitoring: a practical approach to achieving in-situ and site-specific warning of pipeline corrosion and coating failure

An approach to achieving the ambitious goal of cost effectively extending the safe operation life of energy pipelines to, for instance, 100 years is the application of structural health monitoring and life prediction tools that are able to provide long-term remnant pipeline life prediction and in-situ pipeline condition monitoring. A critical step in pipeline structural health monitoring is the enhancement of technological capabilities that are required for quantifying the effects of key factors influencing buried pipeline corrosion and environmentally assisted materials degradation, and the development of condition monitoring technologies that are able to provide in-situ monitoring and site-specific warning of pipeline damage. This paper provides an overview of our current research aimed at developing new sensors for monitoring, categorising and quantifying the level and nature of external pipeline and coating damages under the combined effects of various inter-related variables and processes such as localised corrosion, coating damage and disbondment, cathodic shielding. The concept of in-situ monitoring and site-specific warning of pipeline corrosion is illustrated by a case of monitoring localised corrosion under disbonded coatings using a new corrosion monitoring probe. A basic principle that underpins the use of sensors to monitor localised corrosion has been presented: Localised corrosion and coating failure are not an accidental occurrence, it occurs as the result of fundamental thermodynamic instability of a metal exposed to a specific environment. Therefore corrosion and coating disbondment occurring on a pipeline will also occur on a sensor made of the same material and exposed to the same pipeline condition. Although the exact location of localised corrosion or coating disbondment could be difficult to pinpoint along the length of a buried pipeline, the ‘worst-case scenario’ and high risk pipeline sections and sites are predictable. Sensors can be embedded at these strategic sites to collect data that contain ‘predictor features’ signifying the occurrence of localised corrosion, CP failure, coating disbondment and degradation. Information from these sensors will enable pipeline owners to prioritise site survey and inspection operations, and to develop maintenance strategy to manage aged pipelines, rather than replace them.