Found-Footage Horror and the Frame's Undoing

This essay finds in the found-footage horror cycle an alternative way of understanding the relationship between horror films and reality, which is usually discussed in terms of allegory. I propose the investigation of framing, understood both figuratively (framing the film as documentary) and stylistically (the framing in handheld cameras and in static long takes), as a device that playfully de-stabilizes the separation between the film and the surrounding world. The essay’s main case study is the Paranormal Activity franchise, but examples are drawn from a variety of films

Kit receptor tyrosine kinase dysregulations in feline splenic mast cell tumours

This study investigated Ki t receptor dysregulations (cytoplasmic immunohistochemical expression and/or c-KIT mutations) in cats a\ufb00ected with splenic mast cell tumours. Twenty-two cats were included. Median survival time was 780 days (range: 1\u20131219). An exclusive splenic involvement was signi\ufb01cantly (P = 0.042) associated with longer survival (807 versus 120 days). Eighteen tumours (85.7%) showed Kit cytoplasmic expression (Kit pattern 2, 3). Mutation analysis was successful in 20 cases. Fourteen missense mutations were detected in 13 out of 20 tumours (65%). Eleven (78.6%) were located in exon 8, and three (21.6%) in exon 9. No mutations were detected in exons 11 and 17. Seven mutations corresponded to the same internal tandem duplication in exon 8 (c.1245_1256dup). Although the association between Kit cytoplasmic expression and mutations was signi\ufb01cant, immunohistochemistry cannot be considered a surrogate marker for mutation analysis. No correlation was observed between c-Kit mutations and tumour di\ufb00erentiation, mitotic activity or survival

Experimental investigation on synthesis, characterization, stability, thermo-physical properties and rheological behavior of MWCNTs-kapok seed oil based nanofluid

Several researchers devoted their efforts for the thermal conductivity enhancement of Carbon Nanotubes (CNTs) based nanofluids as CNTs have excellent thermal properties. However, limited research is reported on the detailed thermo-physical properties of CNTs and oil based nanofluids. In this work, the one-step method synthesis of a new MWCNTs-Kapok seed oil based nanofluid at constant nanoparticle concentration (0.1 wt./wt.) is reported. The nanofluid is characterized by FESEM, FTIR, visual stability analysis and thermophysical properties are experimentally measured. The viscosity found in the range of (0.049–10.101¿Pa·s), the thermal conductivity of (0.165–0.207¿W/m·K) and enhancement of thermal conductivity (6.1538%) were observed. Moreover, the viscosity decreases, and thermal conductivity increases with an increase in temperature. The experimentally obtained data are found in agreement with existing models and modified correlations. The rheological behavior showed that nanofluid is non-Newtonian in nature and exhibiting shear thinning or pseudo plastic behavior.Preprin

ZnO Materials as Effective Anodes for the Photoelectrochemical Regeneration of Enzymatically Active NAD+

This work reports the study of ZnO-based anodes for the photoelectrochemical regeneration of the oxidized form of nicotinamide adenine dinucleotide (NAD+). The latter is the most important coenzyme for dehydrogenases. However, the high costs of NAD+ limit the use of such enzymes at the industrial level. The influence of the ZnO morphologies (flower-like, porous film, and nanowires), showing different surface area and crystallinity, was studied. The detection of diluted solutions (0.1 mM) of the reduced form of the coenzyme (NADH) was accomplished by the flower-like and the porous films, whereas concentrations greater than 20 mM were needed for the detection of NADH with nanowire-shaped ZnO-based electrodes. The photocatalytic activity of ZnO was reduced at increasing concentrations of NAD+ because part of the ultraviolet irradiation was absorbed by the coenzyme, reducing the photons available for the ZnO material. The higher electrochemical surface area of the flower-like film makes it suitable for the regeneration reaction. The illumination of the electrodes led to a significant increase on the NAD+ regeneration with respect to both the electrochemical oxidation in dark and the only photochemical reaction. The tests with formate dehydrogenase demonstrated that 94% of the regenerated NAD+ was enzymatically active

Impact dynamics of large dimensional systems

systems. Early version, also known as pre-print Link to publication record in Explore Bristol Researc

Deep Learning Assisted Robust Detection Techniques for a Chipless RFID Sensor Tags

In this paper, we present a new approach for robust reading of identification and sensor data from chipless RFID sensor tags. For the first time, Machine Learning (ML) and Deep Learning (DL) regression modelling techniques are applied to a dataset of measured Radar Cross Section (RCS) data that has been derived from large-scale robotic measurements of custom-designed, 3-bit chipless RFID sensor tags. The robotic system is implemented using the first-of-its-kind automated data acquisition method using an ur16e industry-standard robot. A large data set of 9,600 Electromagnetic (EM) RCS signatures collected using the automated system is used to train and validate four ML models and four 1-dimensional Convolutional Neural Network (1D CNN) architectures. For the first time, we report an end-to-end design and implementation methodology for robust detection of identification (ID) and sensing data using ML/DL models. Also, we report, for the first time, the effect of varying tag surface shapes, tilt angles, and read ranges that were incorporated into the training of models for robust detection of ID and sensing values. The results show that all the models were able to generalise well on the given data. However, the 1D CNN models outperformed the conventional ML models in the detection of ID and sensing values. The best 1D CNN model architectures performed well with a low Root Mean Square Error (RSME) of 0.061 (0.87%) for tag ID and 0.0241 (3.44%) error for the capacitive sensing