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Intellectual Resistance: Paul Schiemanns Rejection of "the New Nationalist Wave"
Get PDFYesPaul Schiemann’s name is well-known only in relatively small academic circles, for example among historians interested in Latvia, the Baltic states and German national minorities. He had formidable intellectual strength, clear moral vision and substantial personal courage, all of which enabled him to resist the rise of Nazism among German national minorities. This paper explains Schiemann’s world view, together with his attempts to promote values of tolerance and justice in the face of destructive nationalism
Re-evaluating archaeomagnetic dates of the vitrified hillforts of Scotland
Get PDFYesA re-analysis of archaeomagnetic data from seven vitrified hillforts in Scotland, sampled in the 1980s, shows excellent agreement with recent radiocarbon dates. In the past thirty years our knowledge of the secular variation of the geomagnetic field has greatly improved, especially in the 1st millennium BC, allowing earlier archaeomagnetic data to be reconsidered. We evaluate the likelihood of the data with respect to a state-of-the-art field geomagnetic model and find close coherence between the observed directions and the model for the closing centuries of the first millennium BC. A new Bayesian method of calibration gives the most likely number of separate events required to produce a series of magnetic directions. We then show that the burning of three of the four oblong forts most likely took place around the same time, and our estimate for the date of this is indistinguishable from recent radiocarbon dates from another fort of similar type
Lotus-leaf inspired surfaces: hydrophobicity evolution of replicas due to mechanical cleaning and mold wear
Get PDFYesInspired from the low wetting properties of Lotus leaves, the fabrication of dual micro/nano-scale topographies is of interest to many applications. In this research, superhydrophobic surfaces are fabricated by a process chain combining ultrashort pulsed laser texturing of steel inserts and injection moulding to produce textured polypropylene parts. This manufacturing route is very promising and could be economically viable for mass production of polymeric parts with superhydrophobic properties. However, surface damages, such as wear and abrasion phenomena, can be detrimental to the attractive wetting properties of replicated textured surfaces. Therefore, the final product lifespan is investigated by employing mechanical cleaning of textured polypropylene surfaces with multipurpose cloths following the ASTM D3450 standard. Secondly, the surface damage of replication masters after 350 injection moulding cycles with glass-fiber reinforced polypropylene, especially to intensify mould wear, was investigated. In both cases, the degradation of the dual-scale surface textures had a clear impact on surface topography of the replicas and thus on their wetting properties, too.Europe Union H2020 research and innovation programme
Endocrine drivers of photoperiod response
Get PDFYesLife in a seasonally variable environment has evolved to interpret the time of year through day length (photoperiod) which is translated into a neurochemical signal. In mammals, the pars tuberalis is a key site where seasonal time signal (melatonin) interfaces and relays photoperiodic information to the hypothalamus via thyrotropin. Recent work has elucidated a potential circannual clock in ‘calendar cells’ of the pars tuberalis. In the hypothalamus, tanycytes are an integral part of the hypothalamic network. Previous studies show the importance of local synthesis of thyroid hormone and retinoic acid in tanycytes. Recently novel downstream neuroendocrine signals, e.g. VGF, FGF21 and chemerin, were identified to govern seasonally appropriate phenotype. Additionally, the hypothalamic-pituitary-growth axis has been implicated in seasonally bodyweight and torpor regulation. Here, we will focus on the endocrine drivers of photoperiod response and highlight novel downstream effects on bodyweight and growth focusing on recent findings from seasonal rodent studies
Temporal rate is not a distinct perceptual metric.
Get PDFYesSensory adaptation experiments have revealed the existence of ‘rate after-effects’ - adapting to a relatively fast rate makes an intermediate test rate feel slow, and adapting to a slow rate makes the same moderate test rate feel fast. The present work aims to deconstruct the concept of rate and clarify how exactly the brain processes a regular sequence of sensory signals. We ask whether rate forms a distinct perceptual metric, or whether it is simply the perceptual aggregate of the intervals between its component signals. Subjects were exposed to auditory or visual temporal rates (a ‘slow’ rate of 1.5 Hz and a ‘fast’ rate of 6 Hz), before being tested with single unfilled intervals of varying durations. Results show adapting to a given rate strongly influences the perceived duration of a single empty interval. This effect is robust across both interval reproduction and duration discrimination judgments. These findings challenge our understanding of rate perception. Specifically, they suggest that contrary to some previous assertions, the perception of sequence rate is strongly influenced by the perception of the sequence’s component duration intervals.This work was supported by a Wellcome Trust [WT097387] grant to NW
Flexural performance of concrete beams reinforced with steel-FRP composite bars
Get PDFYesFlexural performance of concrete beams reinforced with steel-FRP composite bar (SFCB) was investigated in this paper. Eight concrete beams reinforced with different bar types, namely one specimen reinforced with steel bars, one with fiber-reinforced polymer (FRP) bars and four with SFCBs, while the last two with hybrid FRP/steel bars, were tested to failure. Test results showed that SFCB/hybrid reinforced specimens exhibited improved stiffness, reduced crack width and larger bending capacity compared with FRP-reinforced specimen. According to compatibility of strains, materials' constitutive relationships and equilibrium of forces, two balanced situations, three different failure modes and balanced reinforcement ratios as well as analytical technique for predicting the whole loading process are developed. Simplified formulas for effective moment of inertia and crack width are also proposed. The predicted results are closely correlated with the test results, confirming the validity of the proposed formulas for practical use.National Natural Science Foundation of China (51678514), China Postdoctoral Science Foundation (2018M642335), the Science and Technology Project of Jiangsu Construction System (2018ZD047), the Cooperative Education Project of Ministry of Education, China (201901273053), the Blue Project Youth Academic Leader of Colleges and Universities in Jiangsu Province (2020), the Six Talent Peaks Project of Jiangsu Province (JZ038, 2016) and the Yangzhou University Top Talents Support Projec
Blockchain for next generation services in banking and finance: cost, benefit, risk and opportunity analysis
Get PDFYesPurpose – The purpose of this paper is to help in providing a better understanding of the application of blockchain technology in the context of the banking and finance sectors. The aim is to outline blockchain’s benefits, opportunities, costs, risks as well as challenges of the technology in the context of banking and finance services
Design/methodology/approach – Careful examination of the extant literature, including utilising relevant academic-based research databases has been carried out. It covered reviewing various research contributions published in peer-reviewed journals, academic reports, as well as technical reports to help in identifying related benefits, opportunities, costs, and risks.
Findings – The findings reveal that there are limited contributions in utilising blockchain in the banking and finance sectors when compared with other sectors. As such, the study highlighted the relevant perspective of benefits, opportunities, costs, and risks within such sectors.
Practical implications – This study helps in offering a focal point to banking and financial sector managers and decision-makers for realising the benefits of blockchain technology as well as developing strategies and programmes to overcome the identified challenges.
Originality/value – This study highlights the need for a holistic understanding of the various aspects of cost, benefits, risk and opportunities to create blockchain applications that work for banking and finance sectorsNPRP grant # [11S-0117–180325] from the Qatar National Research Fund (a member of Qatar Foundation)
Dynamic Fault Tree Analysis: State-of-the-Art in Modeling, Analysis, and Tools
Get PDFYesSafety and reliability are two important aspects of dependability that are needed to be rigorously evaluated throughout the development life-cycle of a system. Over the years, several methodologies have been developed for the analysis of failure behavior of systems. Fault tree analysis (FTA) is one of the well-established and widely used methods for safety and reliability engineering of systems. Fault tree, in its classical static form, is inadequate for modeling dynamic interactions between components and is unable to include temporal and statistical dependencies in the model. Several attempts have been made to alleviate the aforementioned limitations of static fault trees (SFT). Dynamic fault trees (DFT) were introduced to enhance the modeling power of its static counterpart. In DFT, the expressiveness of fault tree was improved by introducing new dynamic gates. While the introduction of the dynamic gates helps to overcome many limitations of SFT and allows to analyze a wide range of complex systems, it brings some overhead with it. One such overhead is that the existing combinatorial approaches used for qualitative and quantitative analysis of SFTs are no longer applicable to DFTs. This leads to several successful attempts for developing new approaches for DFT analysis. The methodologies used so far for DFT analysis include, but not limited to, algebraic solution, Markov models, Petri Nets, Bayesian Networks, and Monte Carlo simulation. To illustrate the usefulness of modeling capability of DFTs, many benchmark studies have been performed in different industries. Moreover, software tools are developed to aid in the DFT analysis process. Firstly, in this chapter, we provided a brief description of the DFT methodology. Secondly, this chapter reviews a number of prominent DFT analysis techniques such as Markov chains, Petri Nets, Bayesian networks, algebraic approach; and provides insight into their working mechanism, applicability, strengths, and challenges. These reviewed techniques covered both qualitative and quantitative analysis of DFTs. Thirdly, we discussed the emerging trends in machine learning based approaches to DFT analysis. Fourthly, the research performed for sensitivity analysis in DFTs has been reviewed. Finally, we provided some potential future research directions for DFT-based safety and reliability analysis
Attention-based LSTM network for rumor veracity estimation of tweets
Get PDFYesTwitter has become a fertile place for rumors, as information can spread
to a large number of people immediately. Rumors can mislead public opinion,
weaken social order, decrease the legitimacy of government, and lead to a significant threat to social stability. Therefore, timely detection and debunking rumor are
urgently needed. In this work, we proposed an Attention-based Long-Short Term
Memory (LSTM) network that uses tweet text with thirteen different linguistic
and user features to distinguish rumor and non-rumor tweets. The performance of
the proposed Attention-based LSTM model is compared with several conventional
machine and deep learning models. The proposed Attention-based LSTM model
achieved an F1-score of 0.88 in classifying rumor and non-rumor tweets, which
is better than the state-of-the-art results. The proposed system can reduce the
impact of rumors on society and weaken the loss of life, money, and build the firm
trust of users with social media platforms