Sport psychologists’ experiences of organizational stressors

This study extends stress research by exploring sport psychologists’ experiences of organizational stressors. Twelve accredited sport psychologists (6 academics and 6 practitioners) were interviewed regarding their experiences of organizational stress within their jobs. Content analysis involved categorizing the demands associated primarily and directly with their occupation under one of the following general dimensions: factors intrinsic to sport psychology, roles in the organization, sport relationships and interpersonal demands, career and performance development issues, and organizational structure and climate of the profession. A frequency analysis revealed that academics (ΣAOS = 201) experienced more organizational stressors than practitioners (ΣPOS = 168). These findings indicate that sport psychologists experience a wide variety of organizational stressors across different roles, some of which parallel those found previously in other professions. The practical implications for the management of stress for sport psychologists are discussed

Reading Between the Lines

The non-normative structural possibilities of poetry, with its focus on emotion, imagery and sound, makes it a useful way to portray inner experiences that are difficult to express through traditionally descriptive, more prosaic language. As a lecturer, artistic designer and researcher with dyslexia I have often had to use alternative paths to succeed professionally. Both professionally and privately I share arising complexities of my inner intellectual and felt life through poetry. This is a flow of consciousness about my dyslexia

Landing site reachability and decision making for UAS forced landings

After a huge amount of success within the military, the benefits of the use of unmanned aerial systems over manned aircraft is obvious. They are becoming cheaper and their functions advancing to such a point that there is now a large drive for their use by civilian operators. However there are a number of significant challenges that are slowing their inevitable integration into the national airspace systems of countries. A large array of emergency situations will need to be dealt with autonomously by contingency management systems to prevent potentially deadly incidences. One such emergency situation that will need autonomous intervention, is the total loss of thrust from engine failure. The complex multi faceted task of landing the stricken aircraft at a potentially unprepared site is called a forced landing. This thesis presents methods to address a number of critical parts of a forced landing system for use by an unmanned aerial system. In order for an emergency landing site to be considered, it needs to be within glide range. In order to find a landing site s reachability from the point of engine failure the aircraft s glide performance and a glide path must be known. A method by which to calculate the glide performance, both from aircraft parameters or experiments is shown. These are based on a number of steady state assumptions to make them generic and quick to compute. Despite the assumptions, these are shown to have reasonable accuracy. A minimum height loss path to the landing site is defined, which takes account of a steady uniform wind. While this path is not the path to be flown it enables a measure of how reachable a landing site is, as any extra height the aircraft has once it gets to the site makes a site more reachable. It is shown that this method is fast enough to be run online and is generic enough for use on a range of aircraft. Based on identified factors that make a landing site more suitable, a multi criteria decision making Bayesian network is developed to decide upon which site a unmanned aircraft should land in. It can handle uncertainty and non-complete information while guaranteeing a fast reasonable decision, which is critical in this time sensitive situation. A high fidelity simulation environment and flight test platform are developed in order to test the performance of the developed algorithms. The test environments developed enable rapid prototyping of algorithms not just within the scope of this thesis, but on a range of vehicle types. In simulation the minimum height loss paths show good accuracy, for two completely different types of aircraft. The decision making algorithms show that they are capable of being ran online in a flight test. They make a reasonable decision and are capable of quickly reacting to changing conditions, enabling redirection to a more suitable landing site

A Comparative study of two copper(II) based metal-organic frameworks : Cu2¼(OH)½B4C•8H2O and Cu2Na(OH)B4C•7H2O

This study focussed on two copper(II)-containing metal-organic frameworks (MOFs): Cu2Na(OH)B4C•7H2O and Cu2¼(OH)½B4C•8H2O (B4C = 1,2,4,5- benzenetetracarboxylate). They are both covalent, three-dimensional metalorganic framework polymers containing voids filled with water molecules. Both were characterised by elemental analysis, infrared spectroscopy, X-ray powder diffractometry (both in situ and regular), thermogravimetric analysis, differential scanning calorimetry and X-ray photoelectron spectroscopy. These two MOFs are essentially identical, with the only difference being the substitution of sodium by copper at every 4th site (disordered throughout the crystal). The guest inclusion properties of both MOFs were studied and compared. Although both structures collapse on dehydration, it was observed that Cu2Na(OH)B4C•7H2O is able to take up signifcant amounts of water, methanol and ethanol. All these processes are fully reversible. Car-Parrinello molecular dynamics studies suggest that it is a strong interaction between the oxygen atoms on these molecules with the sodium cation of the MOF that is responsible for this signifcant uptake. In contrast, Cu2¼ (OH)½ B4C•8H2O, the MOF without a sodium cation, did not demonstrate any methanol or ethanol uptake, but was able to take up some water. The uptake of water, however, is not a fully reversible process. The absence of sodium likely results in insuffcient energy to draw methanol and ethanol into the framework, while a subtle rotation of a carboxylate group on dehydration decreases the ability of the framework to form hydrogen bonds, thus reducing the ability to take up water. A series of hydrothermal syntheses were performed in order to develop a method of synthesis superior to the current gel-based synthesis that requires several months and has poor yields. The hydrothermal products were characterized by elemental analysis, infrared spectroscopy, X-ray powder diffractometry, thermogravimetric analysis and differential scanning calorimetry. It was shown that the MOF Cu2Na(OH)B4C•7H2O may be synthesised in almost 100% yield by using a temperature of 120°C over a period of 72 hours. It was not possible to synthesise Cu2¼ (OH)½ B4C•8H2O in a 100% yield - it was only obtained as a minor product

The effect of silica on the reduction of precipitated iron-based fischer-tropsch catalysts

Iron Fischer-Tropsch (FT) catalysts are typically prepared as iron oxides which are reduced to FT-active iron metal and iron carbide prior to FT synthesis. The iron oxides contain a variety of different chemical and structural promoters to alter FT-activity. Silica is a common structural promoter which stabilises the formation of small crystallites and provides mechanical integrity to the catalyst. However, silica inhibits the reduction of the oxide precursor to the FT-active phases. This ultimately affects catalyst activity and product selectivity. It has been proposed that the silica interacts with the iron to form encapsulating shells of fayalite (Fe2SiO4), or fayalite rafts between the iron oxide and the silica support. In this study, six silica-promoted iron oxide samples were prepared using a simple co-precipitation technique. Samples contain varying amounts of silica, and the samples are named 100/x Fe/SiO2, where x is the weight of silica for 100 weight iron, with x taking on values of 0, 10, 25, 50, 100 and 200. The resulting iron oxides were characterised using scanning electron microscopy (SEM), transmission electron microscopy (TEM), X-ray powder diffraction (XRPD), M¨ossbauer spectroscopy (MS), magnetic susceptibility measurements (MM), Raman spectroscopy, thermal gravimetric analysis (TGA) and nitrogen physisorption. Their reduction in a hydrogen atmosphere was investigated using temperature programmed reduction (TPR), in situ XRPD and TEM. The reduction in hydrogen of 100/0 Fe/SiO2 and 100/10 Fe/SiO2 was also studied using in situ gas flow TEM cells. These cells allow the samples to be studied in the electron microscope at temperature and pressure conditions approaching those experienced in a real reactor environment. In the absence of a silica promoter (100/0 Fe/SiO2), hematite particles are formed with mean particle diameters of 39 ± 12 and 52.7 ± 0.2 nm determined using TEM and XRPD respectively. MM data reveals a magnetic transition (Morin transition) at≈230 K, consistent with a mean particle size of≈50 nm. In a hydrogen atmosphere, the hematite reduces to metallic iron via a two-step process viz. hematite → magnetite → iron. The final iron particles have an average crystallite size of 68.0 ± 0.2 nm. The presence of lower amounts of silica in the samples 100/10 Fe/SiO2, 100/25 Fe/SiO2 and 100/50 Fe/SiO2 results in the formation of silicasubstituted 2-line ferrihydrite particles. Bands in the Raman spectra of these samples shift on increasing silica content, which indicates an increasing number of Fe-O-Si bonds within the ferrihydrite framework. MM reveals typical superparamagnetic (SPM) behaviour above a blocking temperature in the range 39 - 68 K which gives mean particle sizes of 4.2, 3.6 and 3.5 nm for 100/10 Fe/SiO2, 100/25 Fe/SiO2 and 100/50 Fe/SiO2 respectively, in good agreement with particle sizes determined using TEM (3.1±0.4, 2.4±0.3 and 2.4±0.3 nm respectively). MS data at 300 K and 4.2 K were fitted with distributions of ∆EQ and Bhf respectively. The median values of Bhf decrease with increasing silica content, indicating greater degrees of distortion in the Fe3+ environments induced by increased silica substitution. The reduction to metallic iron occurs via a three-step process viz. hematite → magnetite → wu¨stite → iron, with the silica stabilising the wu¨stite phase. The increasing amount of Fe-O-Si bonds on increasing silica content shifts reduction to higher temperatures broadens each reduction step as a result of local Fe-O-Si concentration variations. Fractions of each sample are not completely reduced even at 1000°C, with the relative proportion increasing with increasing silica content. In situ gas flow TEM studies reveal that the mechanism of reduction involves the liberation of atomic iron atoms from the silica-substituted iron oxides which agglomerate and grow into final iron particles. This leaves a poorly crystalline Fe-O-Si bonded framework behind. STEM-EDS and STEM-EELS reveal low concentrations of silicon at the surface of the resulting iron particles, however they do not form encapsulating shells of fayalite as previously suggested. The majority of the silica remains in the Fe-O-Si material which may crystallise into separate fayalite particles at elevated temperature. The presence of silica in high proportions (100/100 Fe/SiO2 and 100/200 Fe/SiO2) results in the formation of a two-phase system consisting of silicasubstituted 2-line ferrihydrite particles which are encapsulated in an ironinfused amorphous silica network. As with the other silica-bearing samples, there is an increase in Fe-O-Si bonds and an increase in the degree of distortion at Fe3+ sites with increasing silica content. The large amount of silica suppresses the blocking temperature of the SPM crystallites. In a hydrogen atmosphere, the reduction to metallic iron follows the same three step process as the other silica-bearing samples. Reduction temperatures are further shifted to higher values and given reduction steps are considerably broader with increasing silica content. The fraction of iron not fully reduced also increases. Iron particle diameters are very small, since encapsulation by the silica matrix prevents growth of particles

A continuum of weakly coupled oscillatory McKean neurons

The McKean model of a neuron possesses a one dimensional fast voltage-like variable and a slow recovery variable. A recent geometric analysis of the singularly perturbed system has allowed an explicit construction of its phase response curve [S Coombes 2001 Phase-locking in networks of synaptically coupled McKean relaxation oscillators, Physica D, Vol 160, 173-188]. Here we use tools from coupled oscillator theory to study weakly coupled networks of McKean neurons. Using numerical techniques we show that the McKean system has traveling wave phase-locked solutions consistent with that of a network of more biophysically detailed Hodgkin-Huxley neurons

Identification of the Regulatory Logic Controlling Salmonella Pathoadaptation by the SsrA-SsrB Two-Component System

Sequence data from the past decade has laid bare the significance of horizontal gene transfer in creating genetic diversity in the bacterial world. Regulatory evolution, in which non-coding DNA is mutated to create new regulatory nodes, also contributes to this diversity to allow niche adaptation and the evolution of pathogenesis. To survive in the host environment, Salmonella enterica uses a type III secretion system and effector proteins, which are activated by the SsrA-SsrB two-component system in response to the host environment. To better understand the phenomenon of regulatory evolution in S. enterica, we defined the SsrB regulon and asked how this transcription factor interacts with the cis-regulatory region of target genes. Using ChIP-on-chip, cDNA hybridization, and comparative genomics analyses, we describe the SsrB-dependent regulon of ancestral and horizontally acquired genes. Further, we used a genetic screen and computational analyses integrating experimental data from S. enterica and sequence data from an orthologous regulatory system in the insect endosymbiont, Sodalis glossinidius, to identify the conserved yet flexible palindrome sequence that defines DNA recognition by SsrB. Mutational analysis of a representative promoter validated this palindrome as the minimal architecture needed for regulatory input by SsrB. These data provide a high-resolution map of a regulatory network and the underlying logic enabling pathogen adaptation to a host

Unmanned ground operations using semantic image segmentation through a Bayesian network

This paper discusses the machine vision element of a system designed to allow automated taxiing for Unmanned Aerial System (UAS) around civil aerodromes. The purpose of the computer vision system is to provide direct sensor data which can be used to validate vehicle position, in addition to detect potential collision risks. This is achieved through the use of a singular monocular sensor. Untrained clustering is used to segment the visual feed before descriptors of each cluster (primarily colour and texture) are then used to estimate the class. As the competency of each individual estimate can vary based on multiple factors (number of pixels, lighting conditions and even surface type) a Bayesian network is used to perform probabilistic data fusion, in order to improve the classification results. This result is shown to perform accurate image segmentation in real-world conditions, providing information viable for map matching

Boustrophedon coverage path planning for UAV aerial surveys in wind

© 2017 IEEE. In the quickly developing world of precision agriculture UAV remote sensing, there is a need for a greater understanding of winds effect on fixed wing aerial surveying, as this is missing from current literature. This paper presents a method to define and calculate flight times in a Boustrophedon aerial survey coverage path in wind, for a given convex polygon, at a given sweep angle. It is shown that there exists no easy way to define a sweep angle relative to the wind that minimises flight time. This method is validated by comparing the numerical simulated path and times with a number of surveys run in the high fidelity X-Plane simulator

Machine vision for UAS ground operations: using semantic segmentation with a bayesian network classifier

This paper discusses the machine vision element of a system designed to allow Unmanned Aerial System (UAS) to perform automated taxiing around civil aerodromes, with only a monocular camera. The purpose of the computer vision system is to provide direct sensor data which can be used to validate vehicle position, in addition to detecting potential collision risks. In practice, untrained clustering is used to segment the visual feed before descriptors of each cluster (primarily colour and texture) are used to estimate the class. As the competency of each individual estimate can vary dependent on multiple factors (number of pixels, lighting conditions and even surface type). A Bayesian network is used to perform probabilistic data fusion, in order to improve the classification results. This result is shown to perform accurate image segmentation in real-world conditions, providing information viable for localisation and obstacle detection