Identifying safety beliefs among Australian electrical workers

The current study explored underlying beliefs regarding work safety among a sample of experienced Australian electrical workers. A qualitative research methodology using the theory of planned behavior as a framework was employed. A series of interviews and focus groups with licensed electrical workers (N = 46) were analyzed using thematic content analysis. Beliefs were classified as advantages (e.g. personal safety of self and co-workers), disadvantages (e.g., inconvenience to customer/clients and workload), referents (e.g., supervisors, work colleagues, customers), barriers (e.g., time and cost), and facilitators (e.g., training and knowledge, equipment availability) of safety adherence. The belief basis of the theory of planned behavior was a useful framework for exploring workers’ safety beliefs. The identified beliefs can inform future research about the important factors influencing safe work decisions and inform strategies to promote safer workplace decision making within the electrical safety context.

Single layer bismuth iodide: Computational exploration of structural, electrical, mechanical and optical properties

Layered graphitic materials exhibit new intriguing electronic structure and the search for new types of two-dimensional (2D) monolayer is of importance for the fabrication of next generation miniature electronic and optoelectronic devices. By means of density functional theory (DFT) computations, we investigated in detail the structural, electronic, mechanical and optical properties of the single-layer bismuth iodide (BiI3) nanosheet. Monolayer BiI3 is dynamically stable as confirmed by the computed phonon spectrum. The cleavage energy (Ecl) and interlayer coupling strength of bulk BiI3 are comparable to the experimental values of graphite, which indicates that the exfoliation of BiI3 is highly feasible. The obtained stress-strain curve shows that the BiI3 nanosheet is a brittle material with a breaking strain of 13%. The BiI3 monolayer has an indirect band gap of 1.57 eV with spin orbit coupling (SOC), indicating its potential application for solar cells. Furthermore, the band gap of BiI3 monolayer can be modulated by biaxial strain. Most interestingly, interfacing electrically active graphene with monolayer BiI3 nanosheet leads to enhanced light absorption compared to that in pure monolayer BiI3 nanosheet, highlighting its great potential applications in photonics and photovoltaic solar cells.

Electrical conduction in plasma polymerized thin films of γ-terpinene

Plasma polymerized c-terpinene (pp2GT) thin films are fabricated using RF plasma polymerization. MIM structures are fabricated and using the capacitive structures dielectric properties of the material is studied. The dielectric constant values are found to be in good agreement with those determined from ellipsometric data. At a frequency of 100 kHz, the dielectric constant varies with RF deposition power, from 3.69 (10 W) to 3.24 (75 W). The current density–voltage (J2V) characteristics of pp–GT thin films are investigated as a function of RF deposition power at room temperature to determine the resistivity and DC conduction mechanism of the films. At higher applied voltage region, Schottky conduction is the dominant DC conduction mechanism. The capacitance and the loss tangent are found to be frequency dependent. The conductivity of the pp2GT thin films is found to decrease from 1.39 3 10212 S/cm (10 W) to 1.02 3 10213 S/cm (75 W) and attributed to the change in the chemical composition and structure of the polymer. The breakdown field for pp–GT thin films increases from 1.48 MV/cm (10 W) to 2 MV/cm (75 W). A single broad relaxation peak is observed indicating the contribution of multiple relaxations to the dielectric response for temperature dependent J2V. The distribution of these relaxation times is determined through regularization methods. VC 2015 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2015, 132, 42318.

Low-frequency electrical stimulation combined with a cooling vest improves recovery of elite kayakers following a simulated 1000-m race in a hot environment

This study compared the effects of a low-frequency electrical stimulation (LFES; Veinoplus® Sport, Ad Rem Technology, Paris, France), a low-frequency electrical stimulation combined with a cooling vest (LFESCR) and an active recovery combined with a cooling vest (ACTCR) as recovery strategies on performance (racing time and pacing strategies), physiologic and perceptual responses between two sprint kayak simulated races, in a hot environment (∼32 wet-bulb-globe temperature). Eight elite male kayakers performed two successive 1000-m kayak time trials (TT1 and TT2), separated by a short-term recovery period, including a 30-min of the respective recovery intervention protocol, in a randomized crossover design. Racing time, power output, and stroke rate were recorded for each time trial. Blood lactate concentration, pH, core, skin and body temperatures were measured before and after both TT1 and TT2 and at mid- and post-recovery intervention. Perceptual ratings of thermal sensation were also collected. LFESCR was associated with a very likely effect in performance restoration compared with ACTCR (99/0/1%) and LFES conditions (98/0/2%). LFESCR induced a significant decrease in body temperature and thermal sensation at post-recovery intervention, which is not observed in ACTCR condition. In conclusion, the combination of LFES and wearing a cooling vest (LFESCR) improves performance restoration between two 1000-m kayak time trials achieved by elite athletes, in the heat.

Assessment of crop insect damage using unmanned aerial systems: A machine learning approach

Agricultural pests are responsible for millions of dollars in crop losses and management costs every year. In order to implement optimal site-specific treatments and reduce control costs, new methods to accurately monitor and assess pest damage need to be investigated. In this paper we explore the combination of unmanned aerial vehicles (UAV), remote sensing and machine learning techniques as a promising technology to address this challenge. The deployment of UAVs as a sensor platform is a rapidly growing field of study for biosecurity and precision agriculture applications. In this experiment, a data collection campaign is performed over a sorghum crop severely damaged by white grubs (Coleoptera: Scarabaeidae). The larvae of these scarab beetles feed on the roots of plants, which in turn impairs root exploration of the soil profile. In the field, crop health status could be classified according to three levels: bare soil where plants were decimated, transition zones of reduced plant density and healthy canopy areas. In this study, we describe the UAV platform deployed to collect high-resolution RGB imagery as well as the image processing pipeline implemented to create an orthoimage. An unsupervised machine learning approach is formulated in order to create a meaningful partition of the image into each of the crop levels. The aim of the approach is to simplify the image analysis step by minimizing user input requirements and avoiding the manual data labeling necessary in supervised learning approaches. The implemented algorithm is based on the K-means clustering algorithm. In order to control high-frequency components present in the feature space, a neighbourhood-oriented parameter is introduced by applying Gaussian convolution kernels prior to K-means. The outcome of this approach is a soft K-means algorithm similar to the EM algorithm for Gaussian mixture models. The results show the algorithm delivers decision boundaries that consistently classify the field into three clusters, one for each crop health level. The methodology presented in this paper represents a venue for further research towards automated crop damage assessments and biosecurity surveillance.