Clinical legal education (CLE) is potentially the major disruptor of traditional law schools’ core functions. Good CLE challenges many central clichés of conventional learning in law—everything from ...case book method to the 50-minute lecture. And it can challenge a contemporary overemphasis on screen-based learning, particularly when those screens only provide information and require no interaction. Australian Clinical Legal Education comes out of a thorough research program and offers the essential guidebook for anyone seeking to design and redesign accountable legal education; that is, education that does not just transform the learner, but also inculcates in future lawyers a compassion for and service of those whom the law ought to serve. Established law teachers will come to grips with the power of clinical method. Law students struggling with overly dry conceptual content will experience the connections between skills, the law and real life. Regulators will look again at law curricula and ask law deans ‘when’?
Metrology has been successfully used in the last decade to quantify use-wear on stone tools. Such techniques have been mostly applied to fine-grained rocks (chert), while studies on coarse-grained ...raw materials have been relatively infrequent. In this study, confocal microscopy was employed to investigate polished surfaces on a coarse-grained lithology, quartzite. Wear originating from contact with five different worked materials were classified in a data-driven approach using machine learning. Two different classifiers, a decision tree and a support-vector machine, were used to assign the different textures to a worked material based on a selected number of parameters (Mean density of furrows, Mean depth of furrows, Core material volume-Vmc). The method proved successful, presenting high scores for bone and hide (100%). The obtained classification rates are satisfactory for the other worked materials, with the only exception of cane, which shows overlaps with other materials. Although the results presented here are preliminary, they can be used to develop future studies on quartzite including enlarged sample sizes.
Image dehazing is an increasingly widespread approach to address the degradation of images of the natural environment by low-visibility weather, dust and other phenomena. Advances in autonomous ...systems and platforms have increased the need for low-complexity, high-performing dehazing techniques. However, while recent learning-based image dehazing approaches have significantly increased the dehazing performance, this has often been at the expense of complexity and hence the use of prior-based approaches persists, despite their lower performance. This paper addresses both these aspects and focuses on single image dehazing, the most practical class of techniques. A new Dark Channel Prior-based single image dehazing algorithm is presented that has an improved atmospheric light estimation method and a low-complexity morphological reconstruction. In addition, a novel, lightweight end-to-end network is proposed, that avoids information loss and significant computational effort by eliminating the pooling and fully connected layers. Qualitative and quantitative evaluations show that our proposed algorithms are competitive with, or outperform, state-of-the-art techniques with significantly lower complexity, demonstrating their suitability for use in resource-constrained platforms.
This paper draws on the results of 48 focus group discussions carried out across 7 European study countries to shed light on the public understanding of farm animal welfare; however the account that ...we provide does not follow typical social-scientific conventions. We do not try to ‘capture’ public opinion on this issue, as a survey might seek to do by fixing, stabilising and ‘representing’ its subject matter, nor do we attempt to produce an entirely ‘coherent’ version of what the public understands by farm animal welfare. Instead, we adopt a performative approach (see Mol, 2002; Law, 2004; Callon et al., 2009). This enables us both to explore the ways in which lay knowledges are grounded in everyday socio-material practices (such as shopping for food, cooking and eating) and to critically reflect upon how our scholarly attempts to engage with these lay understandings actively intervene with them and help to generate new hybrid knowledges that are partly public and partly academic. More specifically, we identify three distinct acts of knowledge production that took place within the focus group discussions and we dedicate a considerable amount of time and attention to describing the contexts in which and through which each act of knowledge production was choreographed (Cussins, 1996; Thomson, 2005). We then outline what specific versions of farm animal welfare were being enacted within these particular discussions and through these particular contexts. Whilst this method reveals certain overlaps and consistencies between the different ‘knowledge acts’ or ‘ways of knowing’ farm animal welfare, it also reveals some startling contradictions and non-coherencies.
Contemporary European consumers find themselves at an interesting point in history with regards to their relationships with animals. On the one hand there has been a growth in the acknowledgement of ...animal sentience, yet on the other hand, largely unabated, we continue to farm, kill, and eat animals for food. In this paper we contend that these ambiguities are played out within everyday embodied practices of preparing, eating, and shopping for food. We begin our account by outlining a novel performative approach to food consumption practices, which we have termed ‘foodsensing’, and we contend that every act of sensing food is always already an act of making sense of food. This approach allows us to examine the complex interplay between material and symbolic dimensions of food consumption practices. Throughout the paper we draw on this notion of foodsensing, in conjunction with empirical material taken from forty-eight focus group discussions conducted across seven European countries, to shed new light on the ways in which farm animals are made to matter (and not matter) within food consumption practices.
The key problem restricting lithic microwear analysis is the lack of quantitative analysis to support qualitative assessments of different wear traces. This paper presents the reflective laser ...scanning confocal microscope (LSCM) as a new technique for the study of lithic microwear that has the potential to resolve this problem. Firstly, an example is presented that shows how the LSCM compares with conventional reflected light microscopy and scanning electron microscopy. This shows that images, rivalling that of the SEM, can be produced in similar timescales to conventional photomicrography and with no need for casting or sample preparation. The LSCM is also used to measure surface roughness of use-wear produced from working hide (dry, fresh and greasy), woodworking and antler working. This analysis demonstrates clear differences between the different wear polishes and the potential of the LSCM as a quantitative approach in lithic microwear research.
Shamanic belief systems represent the first form of religious practice visible within the global archaeological record. Here we report on the earliest known evidence of shamanic costume: modified red ...deer crania headdresses from the Early Holocene site of Star Carr (c. 11 kya). More than 90% of the examples from prehistoric Europe come from this one site, establishing it as a place of outstanding shamanistic/cosmological significance. Our work, involving a programme of experimental replication, analysis of macroscopic traces, organic residue analysis and 3D image acquisition, metrology and visualisation, represents the first attempt to understand the manufacturing processes used to create these artefacts. The results produced were unexpected--rather than being carefully crafted objects, elements of their production can only be described as expedient.
A new color edge detector based on vector differences is proposed. The basic technique gives as its output the maximum distance between the vectors within a mask. When applied to scalar-valued ...images, the method reduces to the classic morphological gradient. The technique is relatively computationally efficient and can also be readily applied to other vector-valued images. To improve the performance in the presence of noise, a novel pairwise outlier rejection scheme is employed. A quantitative evaluation using Pratt's figure of merit shows the new technique to outperform other recently proposed color edge detectors. In addition, application to real images demonstrates the approach to be highly effective despite its low complexity.
The potential of the nasal region for expression robust 3D face recognition is thoroughly investigated by a novel five-step algorithm. First, the nose tip location is coarsely detected and the face ...is segmented, aligned and the nasal region cropped. Then, a very accurate and consistent nasal landmarking algorithm detects seven keypoints on the nasal region. In the third step, a feature extraction algorithm based on the surface normals of Gabor-wavelet filtered depth maps is utilised and, then, a set of spherical patches and curves are localised over the nasal region to provide the feature descriptors. The last step applies a genetic algorithm-based feature selector to detect the most stable patches and curves over different facial expressions. The algorithm provides the highest reported nasal region-based recognition ranks on the FRGC, Bosphorus and BU-3DFE datasets. The results are comparable with, and in many cases better than, many state-of-the-art 3D face recognition algorithms, which use the whole facial domain. The proposed method does not rely on sophisticated alignment or denoising steps, is very robust when only one sample per subject is used in the gallery, and does not require a training step for the landmarking algorithm.
As scaling becomes a key issue for Large Scale Quantum (LSQ) computing, hardware control systems will become increasingly costly in resources. This paper presents a compact Direct Digital Synthesis ...(DDS) architecture for signal generation adapted for spin qubits, which is scalable in terms of waveform accuracy and the number of synchronized channels. The architecture can produce programmable combinations of ramps, frequency combs and Arbitrary Waveform Generation (AWG) at 5 GS/s, with a worst-case digital feedback latency of 76.8 ns. The FPGA-based system is highly configurable and takes advantage of bitstream switching to achieve the high flexibility required for scalable calibration. The architecture also provides GHz rate multiplexed I/Q single-side band (SSB) modulation for scalable reflectometry. This architecture has been validated in hardware on a Xilinx ZCU111 FPGA demonstrating the mixing of complex signals and the quality of the frequency comb generation for multiplexed control and measurement. The key benefits of this design are the increase of controllability of ramps at the Digital to Analog Converter (DAC) frequency and the reduction in memory requirements by several orders of magnitude compared to existing AWG-based architectures. The hardware for a single channel is very compact, 2% of ZCU111 logic resources for one DAC lane in the default configuration, leaving significant circuit resources for integrated feedback, calibration and Quantum Error Correction (QEC).
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