The werewolf in medieval romance

This volume reassesses the use of the werewolf figure in six medieval romances (French, Latin, and Middle English) that date from the twelfth to fourteenth centuries, and carries research of the werewolf into the field of post-humanism through its examination of how medieval authors disperse the identity of the knight across a variety of assemblages that incorporate human and animal bodies, material objects, physical spaces, and political apparatuses, especially sovereign power and feudal structures

DualAttNet: Synergistic fusion of image-level and fine-grained disease attention for multi-label lesion detection in chest X-rays

Chest radiographs are the most commonly performed radiological examinations for lesion detection. Recent advances in deep learning have led to encouraging results in various thoracic disease detection tasks. Particularly, the architecture with feature pyramid network performs the ability to recognise targets with different sizes. However, such networks are difficult to focus on lesion regions in chest X-rays due to their high resemblance in vision. In this paper, we propose a dual attention supervised module for multi-label lesion detection in chest radiographs, named DualAttNet. It efficiently fuses global and local lesion classification information based on an image-level attention block and a fine-grained disease attention algorithm. A binary cross entropy loss function is used to calculate the difference between the attention map and ground truth at image level. The generated gradient flow is leveraged to refine pyramid representations and highlight lesionrelated features. We evaluate the proposed model on VinDr-CXR, ChestX-ray8 and COVID-19 datasets. The experimental results show that DualAttNet surpasses baselines by 0.6% to 2.7% mAP and 1.4% to 4.7% AP50 with different detection architectures. The code for our work and more technical details can be found at https://github.com/xq141839/DualAttNet

Wall Street, the Nazis, and the Crimes of the Deep State

Commentators have observed the unpleasant reappearance of Nazi themes and ideas in the response to COVID-19. There is evidence to suggest that a deliberate attempt is underway to collapse liberal democracy and to replace it with a technocratic form of totalitarianism. In order to make sense of this shocking phenomenon, it is necessary to revisit the support of Anglo-American finance capital for National Socialism as the most ruthless means of crushing working class resistance. Following the failures of deNazification after 1945, the US national security state put in place by Wall Street recruited former Nazis and used Nazi methods (including death squads, torture, false flag terrorism, biochemical warfare, surveillance-based targeting of political opponents, and the mass killing of civilians) to crush international socialism under the pretext of a "Cold War" with the Soviet Union. A transnational deep state was also formed and was responsible for Operation Gladio and the Strategy of Tension in Italy. With the demise of the Soviet Union, a new enemy had to be found in order for the securitization paradigm to continue to function, and 9/11 provided it: terrorism served as the pretext for globalizing the Strategy of Tension and waging imperialist wars. As social tensions mounted between 2015 and 2017, especially in France, terrorist attacks proliferated and soldiers were put on the streets. Nevertheless, protests around the world began to assume socially progressive forms in 2018/19, prompting the shift to the new biosecurity paradigm in 2020. Although the facade of democracy must be maintained for as long as possible, the transnational ruling class now seeks recourse to totalitarianism to keep the global population under control

The Scientific Grand Tour: The Travel Diary of Martin Folkes (1690-1754)

This volume provides a critical edition of an exceptional example of the ‘Scientific Grand Tour’ taken by Martin Folkes. Martin Folkes (1690–1754) was Newton’s protégé, antiquary, mathematician, and the only simultaneous president of the Royal Society and the Society of Antiquaries. In 1733-5, he went on Grand Tour as a scientific ambassador for the Royal Society, demonstrating Newtonian optics to Italian virtuosi. He also measured ancient and Renaissance buildings to understand past architectural engineering and design. His 97-page illustrated diary (in the Bodleian Library at the University of Oxford, shelfmark MS Eng. misc.c.444) also challenges the long-standing, mistaken impression among scholars that the Royal Society was in decline in the eighteenth century. Analysing Folkes’s activities abroad and creating an edition from this source tracing his Italian route provides a novel reading of Newtonianism and the purpose of the Grand Tour as a vehicle for scientific research and statesmanship. The diary reveals that in Venice, Folkes recreated Newton’s experiments in optics for an invited and sceptical audience at the Palazzo Giustiniani, primarily to counter Paduan natural philosopher Giovanni Rizzetti's (1675-1751) claims he could not reproduce the experiments in the refrangibility of light in Newton's Opticks. When in Venice, Folkes also made contact with Anders Celsius (1701-44) and arranged for Celsius to obtain precision scientific instruments used in his expedition with Pierre Louis Maupertuis (1698-1759) to Lapland to measure the shape of the earth by triangulation to prove Newton's theory that the earth was a flattened sphere. At the same time, the diary reflected Folkes's antiquarian interests in historic cartography, architecture and numismatics, not surprising as the Royal Society at this time was also involved in projects that integrated natural philosophy (‘science’) and antiquarianism (history/analysis of past material culture, a form of nascent archaeology) particularly before the re-establishment of the Society of Antiquaries of London in 1717. Folkes was an exemplar of an interdisciplinary virtuoso of the Enlightenment, his scientific grand tour seeing him move seamlessly between disciplines in the arts and sciences

Annus Tenebrosus: Black Monday, faith and political fervour in Early Modern England

Many sectarians in the English Civil War believed in millenarianism and signs of nature became extremely significant to their prophesies of the end of the world, as well as to their promotion of their political and religious agenda. As the importance of chiliastic beliefs grew in the 1650s, the emanations of the luminaries, as well as their interruption in eclipses, for some held even more significant powers. A solar eclipse lasting for 169 seconds in totality on 29 March 1652 OS/8 April 1652 NS, called ‘Black Monday’ in England, or ‘Mirk Monaday’ in Scotland, was utilised by Fifth Monarchists, as well as others with apocalyptic beliefs, as a sign predicting the fall of government and monarchy, the end of the world, and the second coming of Christ. ‘Black Monday’ was the seventeenth-century equivalent of ‘fake news’, containing enough epistemic authority to be plausible (an eclipse did occur), yet used as a vehicle to promote political or religious beliefs. Simply, the eclipsed, invisible sun made fears about the stability of the state and the future of the world even more visible

LACTA: A Lightweight and Accurate Algorithm for Cherry Tomato Detection in Unstructured Environments

Developing cherry tomato detection algorithms for selective harvesting robots faces many challenges due to the influence of various environmental factors such as lighting, water mist, overlap, and occlusion. To this end, we present LACTA, a lightweight and accurate cherry tomato detection algorithm specifically designed for harvesting robot operation in complex environments. Our approach enhances the model’s generalization ability and robustness by selectively expanding the original dataset using a combination of offline and online data augmentation strategies. To effectively capture the small target features of cherry tomatoes, we construct an adaptive feature extraction network (AFEN) that focuses on extracting pertinent feature information to enhance the identification ability. Additionally, the proposed cross-layer feature fusion network (CFFN) preserves the model’s lightweight nature while obtaining richer feature representations. Finally, the integration of efficient decoupled heads (EDH) further enhances the model’s detection performance. Experimental results demonstrate the adaptability and robustness of LACTA, achieving precision, recall, and mAP values of 94%, 92.5%, and 97.3%, respectively. Compared to the original dataset, the offline-online combined data augmentation strategy improves precision, recall, and mAP by 1.6%, 1.7%, and 1.1%, respectively. The AFEN + CFFN network structure significantly reduces computational complexity by 28% and number of parameters by 72%. With a compact size of only 2.88M, the LACTA model can be seamlessly deployed into selective harvesting robots for the automated harvesting of cherry tomatoes in greenhouses. The code is available at https://github.com/ruyounuo/LACT

Belief, Doubt, and Faith in Life After Death

This essay distinguishes between propositional belief and faith and considers the relationship between these two forms of belief, arguing that faith is not an entirely separate form of belief from propositional assent and that it does require a minimal cognitive content. The essay then goes on to consider beliefs about, and faith in, life after death and develops a metaphorical account of this faith using an Aristotelian concept of the soul as a form of life together with a theological understanding of the death of Jesus in the New Testament. It is argued that the truth claims of assertions about life after death are beyond evidential support, but there are strong reasons for doubting the literal truth of such assertions. Faith in life after death however can be considered rational and truth-seeking. The essay concludes that semantic agnosticism is the proper attitude towards belief in life after death and justifies this position against two possible objections

Workplace Absurdity

Organizations have been significantly challenged by absurd practices to the point where people’s everyday experiences of what development means has become meaningless. Whilst Employee Relations and Organizational Psychology researchers tend to posit a relational approach, Organizational Behavior scholars suggest a contents and process-driven approach to minimize the harm. Alternatively, Human Resource Management scholarships tend to adopt a more practice-based approach. Despite the instrumentalized, measurement methods to surface the organizational, performance-orientated benefits of people development using various training measures at meso-organizational level, a more fundamental global level absurdity has been highlighted recently with the wasting of billions of dollars on climate change enunciations. Through three processes involving internalization, externalization and ideologization, this piece highlights how the absurd has been hypernormalized in workplaces by depicting the fantasmatic portrayal of official, public enunciations on development as opposed to staff’s everyday realities. Trapped by workplace absurdity, the piece draws attention to negligent non-western contexts and theorizations as alternative possibilities

Self-Supervised Learning for Visual Relationship Detection through MaskednBounding Box Reconstruction

We present a novel self-supervised approach for representation learning, particularly for the task of Visual Relationship Detection (VRD). Motivated by the effectiveness of Masked Image Modeling (MIM), we propose Masked Bounding Box Reconstruction (MBBR), a variation of MIM where a percentage of the entities/objects within a scene are masked and subsequently reconstructed based on the unmasked objects. The core idea is that, through object-level masked modeling, the network learns context-aware representations that capture the interaction of objects within a scene and thus are highly predictive of visual object relationships. We extensively evaluate learned representations, both qualitatively and quantitatively, in a few-shot setting and demonstrate the efficacy of MBBR for learning robust visual representations, particularly tailored for VRD. The proposed method is able to surpass state-of-the-art VRD methods on the Predicate Detection (PredDet) evaluation setting, using only a few annotated samples. We make our code available at https://github.com/deeplabai/SelfSupervisedVRD

Italian entrepreneurial decision-making under lockdown: the path to resilience

Purpose – This study addresses current research gaps by integrating resilience literature with crisis management theories, focusing on SMEs. Specifically, we examine how the entrepreneurial decision-making process, via the interplay of causation and effectuation logic, impacts a firm’s ability to respond to unpredictable events. Our investigation seeks to unearth the potentially complex interplay between causation and effectuation logic in fostering organisational resilience, particularly in the face of unprecedented disruptions such as the COVID-19 pandemic. Design/methodology/approach – This study includes the responses of 80 Italian entrepreneurs operating in the hospitality sector. The paper deployed a joint analysis through a Partial Least Squares Structural Equation Modelling technique (PLS-SEM) and a Necessary Condition Analysis (NCA) to assess how the decision-making logics impact the entrepreneurs’ decision when reacting to the pandemic. Findings – The findings show that how entrepreneurs make decisions influence how they react to the crisis. Causation was found as a direct cause of resilience and preparedness, and effectuation was a direct cause of resilience and agility. Moreover, causation indirectly caused resilience through preparedness, and effectuation indirectly caused resilience through agility. Finally, both preparedness and agility are direct causes of resilience. Practical implications – Our research generated insights into why and how some SMEs respond more effectively to uncertainty than others. It provides actionable strategies that business owners and managers can employ to enhance their ability to withstand and recover from crises. Originality – This study’s originality and novelty lie in its empirical investigation of the roles of causation and effectuation logic in entrepreneurial decision-making and, consequently, their influence on SME resilience. Focused on the Italian hospitality sector, it provides unique insights into resilience strategies under severe, real-world conditions, contributing to theoretical development and practical applications in crisis management