Finite Element Simulations of stretch-blow moulding with experimental validation over a broad process window

Injection stretch blow moulding is a well-established method of forming thin-walled containers and has been extensively researched for numerous years. This paper is concerned with validating the finite element analysis of the free-stretch-blow process in an effort to progress the development of injection stretch blow moulding of poly(ethylene terephthalate). Extensive data was obtained experimentally over a wide process window accounting for material temperature and air flow rate, while capturing cavity pressure, stretch-rod reaction force and preform surface strain. This data was then used to assess the accuracy of the correlating FE simulation constructed using ABAQUS/Explicit solver and an appropriate viscoelastic material subroutine. Results reveal that the simulation is able to give good quantitative correlation for conditions where the deformation was predominantly equal biaxial whilst qualitative correlation was achievable when the mode of deformation was predominantly sequential biaxial. Overall the simulation was able to pick up the general trends of how the pressure, reaction force, strain rate and strain vary with the variation in preform temperature and air flow rate. The knowledge gained from these analyses provides insight into the mechanisms of bottle formation, subsequently improving the blow moulding simulation and allowing for reduction in future development costs.

Expert players accurately detect an opponent's movement intentions through sound alone

Sounds offer a rich source of information about events taking place in our physical and social environment. However, outside the domains of speech and music, little is known about whether humans can recognize and act upon the intentions of another agent’s actions detected through auditory information alone. In this study we assessed whether intention can be inferred from the sound an action makes, and in turn, whether this information can be used to prospectively guide movement. In two experiments experienced and novice basketball players had to virtually intercept an attacker by listening to audio recordings of that player’s movements. In the first experiment participants had to move a slider, while in the second one their body, to block the perceived passage of the attacker as they would in a real basketball game. Combinations of deceptive and non-deceptive movements were used to see if novice and/or experienced listeners could perceive the attacker’s intentions through sound alone. We showed that basketball players were able to more accurately predict final running direction compared to non-players, particularly in the second experiment when the interceptive action was more basketball specific. We suggest that athletes present better action anticipation by being able to pick up and use the relevant kinematic features of deceptive movement from event-related sounds alone. This result suggests that action intention can be perceived through the sound a movement makes and that the ability to determine another person’s action intention from the information conveyed through sound is honed through practice.

Feasibility, normative heuristics and the proper place of historical responsibility – a reply to Ohndorf et al.

In this comment, we pick up three points raised by Ohndorf et al. (2015) in their reply to our ethical assessment of the German Advisory Council’s Budget Approach (WBGUBA). First, we discuss and clarify the relationship between ethics and political feasibility, highlighting that the way Ohndorf et el. use feasibility creates an unwarranted status quo bias. Second, we explain the proper place historical responsibility should have within the WBGUBA, stressing the fact that the reasons why we choose one policy proposal over another matter. Third, we analyze the limited extent to which a normative heuristic should motivate an ethically ambitious policy proposal like the WBGUBA.

Effectiveness of Community versus Hospital Eye Service follow-up for patients with neovascular age-related macular degeneration with quiescent disease (ECHoES): a virtual non-inferiority trial

OBJECTIVES: To compare the ability of ophthalmologists versus optometrists to correctly classify retinal lesions due to neovascular age-related macular degeneration (nAMD).

DESIGN: Randomised balanced incomplete block trial. Optometrists in the community and ophthalmologists in the Hospital Eye Service classified lesions from vignettes comprising clinical information, colour fundus photographs and optical coherence tomographic images. Participants' classifications were validated against experts' classifications (reference standard).

SETTING: Internet-based application.

PARTICIPANTS: Ophthalmologists with experience in the age-related macular degeneration service; fully qualified optometrists not participating in nAMD shared care.

INTERVENTIONS: The trial emulated a conventional trial comparing optometrists' and ophthalmologists' decision-making, but vignettes, not patients, were assessed. Therefore, there were no interventions and the trial was virtual. Participants received training before assessing vignettes.

MAIN OUTCOME MEASURES: Primary outcome-correct classification of the activity status of a lesion based on a vignette, compared with a reference standard. Secondary outcomes-potentially sight-threatening errors, judgements about specific lesion components and participants' confidence in their decisions.

RESULTS: In total, 155 participants registered for the trial; 96 (48 in each group) completed all assessments and formed the analysis population. Optometrists and ophthalmologists achieved 1702/2016 (84.4%) and 1722/2016 (85.4%) correct classifications, respectively (OR 0.91, 95% CI 0.66 to 1.25; p=0.543). Optometrists' decision-making was non-inferior to ophthalmologists' with respect to the prespecified limit of 10% absolute difference (0.298 on the odds scale). Optometrists and ophthalmologists made similar numbers of sight-threatening errors (57/994 (5.7%) vs 62/994 (6.2%), OR 0.93, 95% CI 0.55 to 1.57; p=0.789). Ophthalmologists assessed lesion components as present less often than optometrists and were more confident about their classifications than optometrists.

CONCLUSIONS: Optometrists' ability to make nAMD retreatment decisions from vignettes is not inferior to ophthalmologists' ability. Shared care with optometrists monitoring quiescent nAMD lesions has the potential to reduce workload in hospitals.

TRIAL REGISTRATION NUMBER: ISRCTN07479761; pre-results registration.

A Generalized Fuzzy Linguistic Model for Predicting Component Concentrations in an Optical Gas Sensing System

Motivated by environmental protection concerns, monitoring the flue gas of thermal power plant is now often mandatory due to the need to ensure that emission levels stay within safe limits. Optical based gas sensing systems are increasingly employed for this purpose, with regression techniques used to relate gas optical absorption spectra to the concentrations of specific gas components of interest (NOx, SO2 etc.). Accurately predicting gas concentrations from absorption spectra remains a challenging problem due to the presence of nonlinearities in the relationships and the high-dimensional and correlated nature of the spectral data. This article proposes a generalized fuzzy linguistic model (GFLM) to address this challenge. The GFLM is made up of a series of “If-Then” fuzzy rules. The absorption spectra are input variables in the rule antecedent. The rule consequent is a general nonlinear polynomial function of the absorption spectra. Model parameters are estimated using least squares and gradient descent optimization algorithms. The performance of GFLM is compared with other traditional prediction models, such as partial least squares, support vector machines, multilayer perceptron neural networks and radial basis function networks, for two real flue gas spectral datasets: one from a coal-fired power plant and one from a gas-fired power plant. The experimental results show that the generalized fuzzy linguistic model has good predictive ability, and is competitive with alternative approaches, while having the added advantage of providing an interpretable model.

Novel temperature-activated, humidity-sensitive optical sensor

A novel, colorimetric, temperature-activated humidity indicator is presented, with a colour change based on the semi-reversible aggregation of thiazine dyes (esp. methylene blue, MB) encapsulated within the polymer, hydroxypropyl cellulose (HPC). The initially purple MB/HPC film is activated by heat treatment at 370 °C for 4 s, at which point the film (with a colour associated with a highly aggregated form of MB; λmax = 530 nm) becomes blue (indicating the presence of monomeric and dimeric MB; i.e. with λmax = 665; 605 nm respectively). The blue, heat-treated MB/HPC films respond to an ambient environment with a relative humidity (RH) exceeding 70% at 21 °C within seconds, returning to their initial purple colour. This colour change is irreversible until the film is heat-treated once more. When exposed to a lower RH of up to ca. 47%, the film is stable in its blue form. In contrast, a MB/HPC film treated only at 220 °C for 15 s also turns a blue colour and responds in the same way to a RH value of ca. 70%, but it is unstable at moderate RH 37-50% values, so that it gradually returns to its purple form over a period of approximately 6 hours. The possible use of the high heat-treated MB/HPC humidity indicator in the packaging of goods that cannot tolerate high RH, such as dry foods and electronics, is discussed.

Towards optical polarization control of laser-driven proton acceleration in foils undergoing relativistic transparency

Control of the collective response of plasma particles to intense laser light is intrinsic to relativistic optics, the development of compact laser-driven particle and radiation sources, as well as investigations of some laboratory astrophysics phenomena. We recently demonstrated that a relativistic plasma aperture produced in an ultra-thin foil at the focus of intense laser radiation can induce diffraction, enabling polarization-based control of the collective motion of plasma electrons. Here we show that under these conditions the electron dynamics are mapped into the beam of protons accelerated via strong charge-separation-induced electrostatic fields. It is demonstrated experimentally and numerically via 3D particle-in-cell simulations that the degree of ellipticity of the laser polarization strongly influences the spatial-intensity distribution of the beam of multi-MeV protons. The influence on both sheath-accelerated and radiation pressure-accelerated protons is investigated. This approach opens up a potential new route to control laser-driven ion sources.

A generalized fuzzy linguistic model for predicting component concentrations in an optical gas sensing system

Motivated by environmental protection concerns, monitoring the flue gas of thermal power plant is now often mandatory due to the need to ensure that emission levels stay within safe limits. Optical based gas sensing systems are increasingly employed for this purpose, with regression techniques used to relate gas optical absorption spectra to the concentrations of specific gas components of interest (NO_x, SO₂ etc.). Accurately predicting gas concentrations from absorption spectra remains a challenging problem due to the presence of nonlinearities in the relationships and the high-dimensional and correlated nature of the spectral data. This article proposes a generalized fuzzy linguistic model (GFLM) to address this challenge. The GFLM is made up of a series of “If-Then” fuzzy rules. The absorption spectra are input variables in the rule antecedent. The rule consequent is a general nonlinear polynomial function of the absorption spectra. Model parameters are estimated using least squares and gradient descent optimization algorithms. The performance of GFLM is compared with other traditional prediction models, such as partial least squares, support vector machines, multilayer perceptron neural networks and radial basis function networks, for two real flue gas spectral datasets: one from a coal-fired power plant and one from a gas-fired power plant. The experimental results show that the generalized fuzzy linguistic model has good predictive ability, and is competitive with alternative approaches, while having the added advantage of providing an interpretable model.