bluuebunny/crossref_metadata_2025 huggingface dataset:
Experimental investigation on seismic performance of the double‐superimposed shear wall with different vertical connections
Authors: Meng Longfei , Zhu Lihua , Sun Rui , Su Hao , Ye Yanhua , Xu Lujun
Published: January 2022

This study investigated the seismic performances of double‐superimposed shear walls (DSSWs). Two types of vertical connections were proposed and investigated for the double‐superimposed wall system. Both vertical connections contain a 400 mm wide concealed column; one is prefabricated connection and the other is a 400 mm thick cast‐in‐place connection. Four samples considering the cast‐in‐place concrete and vertical connections are tested cyclically. The damage and hysteresis characteristics, stiffness, ductility, and energy dissipation capacity of the specimens were analyzed. The failure mode of four spliced walls was bending‐shear failure, and all the walls show good seismic performance. The cast in situ connections with 400 mm thickness performed as well as the prefabricated connections. Then, the seismic performance indicators of DSSWs cast with self‐compacting concrete (SCC) are significantly enhanced compared with those of normal concrete shear walls. The use of SCC and cast‐in‐place vertical connections with 400 mm thickness is recommended, which is more convenient for construction in double‐superimposed wall systems. Furthermore, this study established the calculation models of the bearing capacity, and the calculation results agreed well with the experimental results.
Finite element analysis of punching shear behavior of reinforced concrete slabs supported on walls
Authors: Milligan Graeme J. , Polak Maria Anna , Zurell Cory
Published: January 2022

Due to the low lateral stiffness of slabs supported on columns alone, reinforced concrete flat plates are typically combined with other structural elements, such as shear walls. In these structures, the slab–column connections are designed to carry gravity loads only, and the shear walls are required to resist both gravity and lateral forces. Therefore, the slab–wall connections are essential for the performance of both the gravity and lateral force resisting systems. However, most punching shear research and design provisions are focused on slab–column connections, even though punching failures around slab–wall connections have occurred experimentally. Empirical testing of slab–wall connections is difficult due to the specimen size. This paper investigates the punching shear behavior of interior slab–wall connections subjected to concentric vertical loading, and combined concentric vertical loading and uniaxial unbalanced moment using a plasticity‐based nonlinear finite element model (FEM) in ABAQUS. The analysis of isolated slab–wall connections demonstrates that punching failures can occur before one‐way shear failures. Since the overall connection capacity is much higher than the expected loads in most structures, if these punching failures happen they would be localized to the region around the wall end and are not expected to lead to structural collapse.
Fine structure and transcription dynamics of bread wheat ribosomal DNA loci deciphered by a multi‐omics approach
Authors: Tulpová Zuzana , Kovařík Aleš , Toegelová Helena , Navrátilová Pavla , Kapustová Veronika , Hřibová Eva , Vrána Jan , Macas Jiří , Doležel Jaroslav , Šimková Hana
Published: January 2022

Three out of four RNA components of ribosomes are encoded by 45S ribosomal DNA (rDNA) loci, which are organized as long head‐to‐tail tandem arrays of nearly identical units, spanning several megabases of sequence. Due to this structure, the rDNA loci are the major sources of gaps in genome assemblies, and gene copy number, sequence composition, and expression status of particular arrays remain elusive, especially in complex genomes harboring multiple loci. Here we conducted a multi‐omics study to decipher the 45S rDNA loci in hexaploid bread wheat. Coupling chromosomal genomics with optical mapping, we reconstructed individual rDNA arrays, enabling locus‐specific analyses of transcription activity and methylation status from RNA‐ and bisulfite‐sequencing data. We estimated a total of 6,650 rDNA units in the bread wheat genome, with approximately 2,321, 3,910, 253, and 50 gene copies located in short arms of chromosomes 1B, 6B, 5D, and 1A, respectively. Only 1B and 6B loci contributed substantially to rRNA transcription at a roughly 2:1 ratio. The ratio varied among five tissues analyzed (embryo, coleoptile, root tip, primary leaf, mature leaf), being the highest (2.64:1) in mature leaf and lowest (1.72:1) in coleoptile. Cytosine methylation was considerably higher in CHG context in the silenced 5D locus as compared with the active 1B and 6B loci. In conclusion, a fine genomic organization and tissue‐specific expression of rDNA loci were deciphered, for the first time, in a complex polyploid species. The results are discussed in the context of wheat evolution and transcription regulation.
Longevity of vaccine protection: Immunological mechanism, assessment methods, and improving strategy
Authors: Chen Zhian , Gao Xin , Yu Di
Published: January 2022

Vaccination represents one of the most important achievements in modern medicine. During the era of COVID‐19 pandemic, the successful vaccination for SARS‐COV‐2 is the major hope to bring the society back to normal. However, although vaccines, such as for smallpox and poliomyelitis, can trigger life‐long protection in individuals and help to generate the herd immunity resulting in the eradication of pathogens, other vaccines, with seasonal influenza vaccine as a case in point, are unable to induce sustained immunity so that repeated vaccination is required. As most vaccines were developed empirically, the immunological mechanism underlying the longevity of vaccine‐induced protection remains only partially understood. In this review, we first describe vaccine‐induced humoral immune response in which long‐lived plasma cells and memory B cells are produced. We then summarise methods using immunological correlates of protection to assess the longevity of vaccine efficacy and provide the evidence and knowledge for the duration of protection by current vaccines. Last, we discuss rationale and strategies to improve the duration of vaccine protection by targeting vaccine immunogenicity, antibody affinity, avidity and prime‐boost scheme.
Portable and visual assays for the detection of SARS‐CoV‐2
Authors: Zhang Yufan , Ding Dan
Published: January 2022

Corona virus disease 2019 (COVID‐19) is a serious contagious disease that arises from severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2). The disease is transmitted primarily through droplets transmission, which does not exclude the possibility of transmission through aerosols and digestive tract and other means. The majority of COVID‐19 cases present as common and mild, while a few cases progress rapidly to the severe and critical stage, making it more difficult to save the disease. Current laboratory diagnostic approaches for COVID‐19 are on the basis of pathogenic tests for viral nucleic acids, serological tests by specific antibody detection, and general tests. For now, Real‐time quantitative PCR (qRT‐PCR) is the gold standard for the detection of COVID‐19, but the method is complicated and may have false‐negative results. Therefore, in order to diagnose and prevention COVID‐19 more effectively, it is needful to develop highly sensitive diagnostic methods with portable instruments and visualized results. This mini‐review provides an overview of the current portable and visual assays of detection of COVID‐19, in order to achieve early effective and more accurate diagnosis of COVID‐19.
Distinguishing mobility and immobility when establishing species‐specific activity budgets: A case study with gorillas (Gorilla berengei berengei and Gorilla gorilla gorilla)
Authors: Nsekanabo Jean D. , Leeds Austin , Eckardt Winnie , Tuyisingize Deogratias , Nyiramana Aisha , Lukas Kristen E.
Published: January 2022

Activity budgets characterize the distribution of behavior over a specified time period. In some cases, having comparable data from free‐ranging populations can help inform the management of wildlife in zoos and sanctuaries. For example, although variations exist across subspecies, seasons, and study sites, diurnal activity budgets for free‐ranging gorillas largely consist of feeding and resting. Unfortunately, most studies do not consistently differentiate between the type of activities gorillas exhibit while locomoting versus stationary. Therefore, it can be difficult to characterize optimal levels of aerobic activity that might enhance body condition or promote gorilla health in zoos and sanctuaries. In this study, we concurrently measured the mobility state and activity of mountain gorillas (Gorilla beringei beringei) in Volcanoes National Park, Rwanda. From June to August 2015, behavioral data were collected using group scan sampling with 15‐min intervals in two groups (N = 29 gorillas) monitored by the Dian Fossey Gorilla Fund International. Overall, gorillas spent significantly more time immobile (85.2% of observations) than mobile (14.8%), revealing energy expenditure levels comparable to western lowland gorillas living in zoos. There was no difference in behavioral diversity when gorillas were mobile versus immobile but adult females exhibited substantially less behavioral diversity while immobile than other age‐sex classes. There was more diversity in behaviors following the transition from immobile to mobile than vice versa, particularly for adult females. Future studies should concurrently measure mobility state and behavior to improve the precision of activity budget data and serve as a more useful tool for evaluating optimal activity levels for wildlife in human care.
Poststructuralism in International Relations: Discourse and the Military
Authors: Baumann Mario
Published: January 2022

This chapter introduces the poststructuralist perspective on international relations (IR). It outlines the epistemological and ontological fundament of poststructuralist thinking and introduces key concepts, notably discourse.

This chapter aims to show that the way we talk about the world, about ourselves and others matters. It employs a particular focus on issues and examples that relate to the military – a domain that for long has been dealt with from more traditional IR perspectives. It seeks to encourage to look at those issues from a different, more critical, angle. It touches upon questions like: Can we ever be fully secure or do we need threats? How did the Global War on Terror become thinkable? What is the relationship between humanitarian interventions and identity?

By presenting key contributions to the poststructuralist body of literature in IR, this chapter traces a poststructuralist perspective on issues of international relations, notably the state and foreign policy, security and threats. It encourages to scrutinize them critically and gives an overview of how to employ this theoretical perspective for empirical discourse analyses in practice.
Modelling the Cost and Benefits of Adaptation. A Targeted Review on Integrated Assessment Models with a Special Focus on Adaptation Modelling
Authors: Schwarze Reimund , Oberpriller Quirin , Peter Martin , Füssler Jürg
Published: January 2022

This paper gives a targeted review on Integrated Assessment Models (IAMs) with a focus on damage functions and adaptation modelling.
Dynamic Flood Risk Modelling in Human–Flood Systems
Authors: Kreibich Heidi , Sairam Nivedita
Published: January 2022

Effective flood risk management is highly relevant for advancing climate change adaptation. It needs to be based on risk modelling that considers the dynamics, complex interactions and feedbacks in human–flood systems. In this regard, we review recent advancements in understanding, quantifying and modelling changes in risk and its drivers. A challenge for integrating human behaviour in dynamic risk assessments and modelling is the combined consideration of qualitative and quantitative data. Advancements in this respect are (1) the compilation and analysis of comprehensive qualitative and quantitative data on flood risk changes in case studies following the paired event concept; (2) the integration of qualitative and quantitative data into socio-hydrological models using Bayesian inference; and (3) the coupling of hydrological flood risk models with behaviour models in socio-hydrological modelling systems. We recommend to further develop these approaches and use more such process-based, dynamic modelling also for large-scale flood risk analyses. These approaches are increasingly feasible due to significant improvements in computational power and data science.
Weather and Climate Services to Support a Risk-Sharing Mechanism for Adaptation of the Agricultural Sector. A Theoretical Example for Drought-Prone Areas
Authors: Máñez Costa María , Kovalevsky Dmitry V.
Published: January 2022

Sharing the burden of adaptation is key for the agricultural sector in developing countries. For the agricultural sector in developing countries, the losses will go from 3% under 1.5 °C scenario to 7% under 2 °C scenario (Masson-Delmotte et al. 2018). This anticipated information on possible climate change-driven challenges possesses a big load in farmers management that might ex-ante stop investing because of the negative consequences of the scenarios presented. This situation could be even worse in subsistence farming system totally dependent on the yields. Crop insurances can be a good way to overcome some of the losses. In this paper, we present weather-based insurance schemes (WII), which are based on weather index objectively determined for the specific agricultural region, and therefore the individual loss assessment, which makes insurances too expensive, is not necessary. We present the results of decisions based on perfect and imperfect weather forecasts and conclude by offering insights in the difference of decision-making if a perfect forecast might be available or not and the consequences for farmers income.
Recent Innovations in Flood Hazard Modelling Over Large Data Sparse Regions
Authors: Neal Jeffrey
Published: January 2022

This opinion piece summarises recent progress in the development of global flood models (GFMs) in support of flood impact modelling and identifies potential areas for model improvement over the next 5–10 years. In many parts of the world, flood hazard data are absent or lack the accuracy and precision required for most practical applications, including climate change impact assessment. With the hydrological cycle expected to intensify due to climate change, better modelling of flood hazard is needed as a prerequisite to understanding how flood risk might change in the future with climate. The past decade has seen substantial advances in the modelling of flood inundation in data scarce areas along with the emergence of global flood models that could form the foundation of global impact assessments. In summarising these advances, four key themes emerge linked to topography, extreme flow estimation, river network parameterisation and numerical modelling of inundation. Progress in each of these themes will be needed to deliver the next generation of global flood hazard data.
A Top-Down Meets Bottom-Up Approach for Climate Change Adaptation in Water Resource Systems
Authors: Pulido-Velazquez Manuel , Marcos-Garcia Patricia , Girard Corentin , Sanchis-Ibor Carles , Martinez-Capel Francisco , García-Prats Alberto , Ortega-Reig Mar , García-Mollá Marta , Rinaudo Jean Daniel
Published: January 2022

The adaptation to the multiple facets of climate/global change challenges the conventional means of water system planning. Numerous demand and supply management options are often available, from which a portfolio of adaptation measures needs to be selected in a context of high uncertainty about future conditions. A framework is developed to integrate inputs from the two main approaches commonly used to plan for adaptation. The proposed “top–down meets bottom–up” approach provides a systematic and practical method for supporting the selection of adaptation measures at river basin level by comprehensively integrating the goals of economic efficiency, social acceptability, environmental sustainability, and adaptation robustness. The top-down approach relies on the use of a chain of models to assess the impact of global change on water resources and its adaptive management over a range of climate projections. Future demand scenarios and locally prioritized adaptation measures are identified following a bottom-up approach through a participatory process with the relevant stakeholders and experts. Cost-effective combinations of adaptation measures are then selected using a hydro-economic model at basin scale. The resulting adaptation portfolios are climate checked to define a robust program of measures based on trade-offs between adaptation costs and reliability. Valuable insights are obtained on the use of uncertain climate information for selecting robust, reliable, and resilient water management portfolios. Finally, cost allocation and equity implications are analyzed through the comparison of economically rational results (cooperative game theory) and the application of social justice principles.
Advances in Climate Adaptation Modeling of Infrastructure Networks
Authors: Pant Raghav
Published: January 2022

As the adverse effects of climate change are increasingly becoming unavoidable, calls for improving climate adaptation assessments have gathered interest at the global scale. Infrastructure policymakers and practitioners are now interested in understanding climate vulnerabilities and risks that capture the systemic nature of failure propagation seen across interconnected networks. This would help inform adaptation planning objectives meant to improve systemic resilience. This paper presents recent technical methodological and tool-based advances made in climate vulnerability, risk, and adaptation modeling of large-scale infrastructure networks. These methodologies adopt a bottom-up approach that focuses on creating data-rich representations of infrastructure network attributes, resource flows, and socio-economic indicators that are all used for quantifying direct and indirect risks to network assets exposed to extreme climate hazards at multiple scales. Insights from different case studies are presented to show how such methodologies have been used in practice for informing different policy needs. The paper concludes by identifying the existing gaps and future opportunities for such bottom-up infrastructure network vulnerability, risk, and adaptation assessment methodologies.
Climate Change Adaptation in Insurance
Authors: Scholer Marie , Schuermans Pamela
Published: January 2022

In this paper, we show three examples of how insurers can contribute to climate change adaptation, through insurers’ underwriting and pricing practice. In the context of climate change, there is a clear need to go beyond traditional risk transfer products. Including risk reduction measures in an insurance product has the advantage of helping to better adapt to climate change by not only transferring the risk but by directly reducing avoidable damages when an event strikes, which as a result contributes to build a more resilient society.
Impact-Oriented Climate Information Selection
Authors: van den Hurk Bart
Published: January 2022

To support climate adaptation decision-making, a picture of current and upcoming climate and socio-economic conditions is required, including an overview of intervention scenarios and their impact. In order to be actionable, this picture needs to rely on credible, relevant, and legitimate information, which implies the use of tested models and concepts, tailored to the decision context, and with transparent and understandable assumptions on boundary conditions and process representation. These criteria are challenged when the complexity of the problem is large and stakes are high. For many conditions, unforeseeable features and events with potentially large implications affect the problem at hand and contribute to the uncertainty that is not easily quantified, let alone eliminated. We explore storyline development approaches that help in selecting relevant and credible pathways and events that enrich the understanding of the risks and options at stake. We explore two categories of storylines (climate scenario storylines and climate risk storylines) by discussing use cases in which these were developed.
On the Evaluation of Climate Change Impact Models for Adaptation Decisions
Authors: Wagener Thorsten
Published: January 2022

Detailed understanding of the potential local or regional implications of climate change is required to guide decision- and policy-makers when developing adaptation strategies and designing infrastructure solutions suitable for potential future conditions. Impact models that translate potential future climate conditions into variables of interest (such as drought or flood risk) are needed to create the required causal connection between climate and impact for scenario-based analyses. Recent studies suggest that the main strategy for the validation of such models (and hence the justification for their use) still heavily relies on the comparison with historical observations. In this short paper, the author suggests that such a comparison alone is insufficient and that global sensitivity analysis provides additional possibilities for model evaluation to ensure greater transparency and better robustness of model-based analyses. Global sensitivity analysis can be used to demonstrate that the parameters defining intervention options (such as land use choices) adequately control the model output (even under potential future conditions); it can be used to understand the robustness of model outputs to input uncertainties over different projection horizons, the relevance of model assumptions, and how modelled environmental processes change with climatic boundary conditions. Such additional model evaluation would strengthen the stakeholder confidence in model projections and therefore into the adaptation strategies derived with the help of these model outputs.
Modelling Risk Reduction Measures to Minimise Future Impacts of Storms at Coastal Areas
Authors: Ferreira Óscar
Published: January 2022

Coastal storms often cause damages and losses in occupied areas. Under climate change conditions (i.e. sea-level rise and increased frequency of extreme sea levels) and increasing human occupation, the consequences of coastal storms will be amplified if no adaptation actions are implemented. The selection of the best possible coastal management measures to reduce risks at coastal areas, considering costs, effectiveness and acceptance, will be mandatory in the future. This work presents a generic approach to model disaster risk reduction measures at coastal areas, including climate change effects. The proposed methodology is adaptable to any coastal region and can be used to test (and improve) management options at a broad number of coastal areas. It can also be used to define a timeframe for the implementation of the defined measures since not all risk reduction measures, under a climate change scenario, need to be implemented at the same time. This would help to optimise implementation costs while reducing the risk to the occupation and people.
3D CNN Architectures and Attention Mechanisms for Deepfake Detection
Authors: Roy Ritaban , Joshi Indu , Das Abhijit , Dantcheva Antitza
Published: January 2022

Manipulated images and videos have become increasingly realistic due to the tremendous progress of deep convolutional neural networks (CNNs). While technically intriguing, such progress raises a number of social concerns related to the advent and spread of fake information and fake news. Such concerns necessitate the introduction of robust and reliable methods for fake image and video detection. Toward this in this work, we study the ability of state-of-the-art video CNNs including 3D ResNet, 3D ResNeXt, and I3D in detecting manipulated videos. In addition, and toward a more robust detection, we investigate the effectiveness of attention mechanisms in this context. Such mechanisms are introduced in CNN architectures in order to ensure that robust features are being learnt. We test two attention mechanisms, namely SE-block and Non-local networks. We present related experimental results on videos tampered by four manipulation techniques, as included in the FaceForensics++ dataset. We investigate three scenarios, where the networks are trained to detect (a) all manipulated videos, (b) each manipulation technique individually, as well as (c) the veracity of videos pertaining to manipulation techniques not included in the train set.
Face Morphing Attack Detection Methods
Authors: Scherhag Ulrich , Rathgeb Christian , Busch Christoph
Published: January 2022

Morphing attacks pose a serious threat to face recognition systems, especially in the border control scenario. In order to guarantee a secure operation of face recognition algorithms in the future, it is necessary to be able to reliably detect morphed facial images and thus be able to reject them during enrolment or verification. This chapter provides an overview of morphing attack detection algorithms and metrics to measure and compare their performance. Different concepts of morphing attack detection are introduced and state-of-the-art detection methods are evaluated in a comprehensive cross-database experiments considering various realistic image post-processings.
Practical Evaluation of Face Morphing Attack Detection Methods
Authors: Spreeuwers Luuk , Schils Maikel , Veldhuis Raymond , Kelly Una
Published: January 2022

Face morphing is a technique to combine facial images of two (or more) subjects such that the result resembles both subjects. In a morphing attack, this is exploited by, e.g., applying for a passport with the morphed image. Both subjects who contributed to the morphed image can then travel using this passport. Many state-of-the-art face recognition systems are vulnerable to morphing attacks. Morphing attack detection (MAD) methods are developed to mitigate this threat. MAD methods published in literature are often trained on a limited number of or even a single dataset where all morphed faces are created using the same procedure. The resulting MAD methods work well for these specific datasets, with reported detection rates of over 99%, but their performance collapses for face morphs created using other procedures. Often even simple image manipulations, like adding noise or smoothing cause a serious degradation in performance of the MAD methods. In addition, more advanced tools exist to manipulate the face morphs, like manual retouching or morphing artifacts can be concealed by printing and scanning a photograph (as used in the passport application process in many countries). Furthermore, datasets for training and testing MAD methods are often created by morphing images from arbitrary subjects including even male-female morphs and morphs between subjects with different skin color. Although this may result in a large number of morphed faces, the created morphs are often not convincing and certainly don’t represent a best effort attack by a criminal. A far more realistic attack would include careful selection of subjects that look alike and create high quality morphs from images of these subjects using careful (manual) post-processing. In this chapter we therefore argue that for robust evaluation of MAD methods, we require datasets with morphed images created using a large number of different morphing methods, including various ways to conceal the morphing artifacts by, e.g., adding noise, smoothing, printing and scanning, various ways of pre- and post-processing, careful selection of the subjects and multiple facial datasets. We also show the sensitivity of various MAD methods to the mentioned variations and the effect of training MAD methods on multiple datasets.
Facial Retouching and Alteration Detection
Authors: Majumdar Puspita , Agarwal Akshay , Vatsa Mayank , Singh Richa
Published: January 2022

On the social media platforms, the filters for digital retouching and face beautification have become a common trend. With the availability of easy-to-use image editing tools, the generation of altered images has become an effortless task. Apart from this, advancements in the Generative Adversarial Network (GAN) leads to creation of realistic facial images and alteration of facial images based on the attributes. While the majority of these images are created for fun and beautification purposes, they may be used with malicious intent for negative applications such as deepnude or spreading visual fake news. Therefore, it is important to detect digital alterations in images and videos. This chapter presents a comprehensive survey of existing algorithms for retouched and altered image detection. Further, multiple experiments are performed to highlight the open challenges of alteration detection.
Face Manipulation Detection in Remote Operational Systems
Authors: Pic Marc Michel , Mahfoudi Gaël , Trabelsi Anis , Dugelay Jean-Luc
Published: January 2022

In this chapter, we present the various categories of Face Manipulation and their use within different remote operational systems. We then use the example of remote identity document onboarding systems to illustrate how each category can be used in practice to compromise such a system. After a definition of the different Face Manipulation categories and the common algorithms used to produce them, we go through the various manipulation detection algorithms and common image and video forgery datasets. We then introduce some known counter-forensics methods that can be used by an attacker to avoid detection. Knowing the detection methods and the counter-forensic, we present how we can build up a safer system by using the correct methods at the correct time. But also how knowledge about the tampering process could be used to design the user experience to make the systems harder to compromise. We complete this review by the standardisation effort and legal aspect on the matter. And we conclude by discussing the remaining challenges and perspectives for better use of nowadays detection methods in practical usage.
Promises, Social, and Ethical Challenges with Biometrics in Remote Identity Onboarding
Authors: Laas-Mikko Katrin , Kalvet Tarmo , Derevski Robert , Tiits Marek
Published: January 2022

Issuance of identity documents has commonly relied on face-to-face customer onboarding. Checking a person's physical presence and appearance has been an essential part of identity enrolling procedures to avoid the risk of identity forgery. Yet, several weaknesses, including face morphing attacks, have been identified in document issuing processes. In the context of the COVID-19 pandemic, increasing international mobility, and a greater focus on user convenience, established onboarding rules and procedures have been disrupted. Solutions are being sought which would eliminate the barriers that stem from physical distance while offering at least equal or even better onboarding processes than in-person identity verification. Recently, novel remote onboarding solutions have appeared on the market. They vary from human-assisted video identification procedures to biometric-based automated verification procedures. The main social and ethical issues with biometrics in remote identity onboarding are (1) the risk of harming integrity of personal identity and misuse of it; (2) the risk of privacy invasion and function creep; (3) ethical issues that are raising from algorithmically driven actions and decisions; and (4) public perception and social acceptance of technology. These non-technical requirements need to be addressed in developing identity verification technologies based on biometrical algorithms and security techniques.
The Threat of Deepfakes to Computer and Human Visions
Authors: Korshunov Pavel , Marcel Sébastien
Published: January 2022

Deepfake videos, where a person’s face is automatically swapped with a face of someone else, are becoming easier to generate with more realistic results. The concern for the impact of the widespread deepfake videos on the societal trust in video recordings is growing. In this chapter, we demonstrate how dangerous deepfakes are for both human and computer visions by showing how well these videos can fool face recognition algorithms and naïve human subjects. We also show how well the state-of-the-art deepfake detection algorithms can detect deepfakes and whether they can outperform humans.
Talking Faces: Audio-to-Video Face Generation
Authors: Wang Yuxin , Song Linsen , Wu Wayne , Qian Chen , He Ran , Loy Chen Change
Published: January 2022

Talking face generation aims at synthesizing coherent and realistic face sequences given an input speech. The task enjoys a wide spectrum of downstream applications, such as teleconferencing, movie dubbing, and virtual assistant. The emergence of deep learning and cross-modality research has led to many interesting works that address talking face generation. Despite great research efforts in talking face generation, the problem remains challenging due to the need for fine-grained control of face components and the generalization to arbitrary sentences. In this chapter, we first discuss the definition and underlying challenges of the problem. Then, we present an overview of recent progress in talking face generation. In addition, we introduce some widely used datasets and performance metrics. Finally, we discuss open questions, potential future directions, and ethical considerations in this task.
Detection of AI-Generated Synthetic Faces
Authors: Gragnaniello Diego , Marra Francesco , Verdoliva Luisa
Published: January 2022

In recent years there have been astonishing advances in AI-based synthetic media generation. Thanks to deep learning methods it is now possible to generate visual data with a high level of realism. This is especially true for human faces. Advanced deep learning tools allow one to easily change some specific attributes of a real face or even create brand new identities. Although this opens up a large number of new opportunities, just think of the entertainment industry, it also undermines the trustworthiness of media content and supports the spread of fake identities over the internet. In this context, there is a fundamental need to develop robust and automatic tools capable of distinguishing synthetic faces from real ones. The scientific community is making a huge research effort in this field, proposing several interesting approaches. However, a universal detector is yet to come. Fundamentally, the research in this field is like a cat and mouse game, with new detectors that are designed to deal with powerful synthetic face generators, while the latter keep improving to produce more and more realistic images. In this chapter we will present the most effective techniques proposed in the literature for the detection of synthetic faces. We will analyze their rationale, present real-world application scenarios , and compare different approaches in terms of accuracy and generalization ability.
Understanding the Basics of Aviation Noise
Authors: Gély Denis , Márki Ferenc
Published: January 2022

This chapter deals with the description of the physical mechanisms of noise, the noise perception and the annoyance induced by air traffic in the aeronautics domain. The authors introduce the basics of aviation noise, describe the main characteristics of the noise emitted by an aircraft in flight, recall the fundamental laws of the audition and noise perception and present the specific context for the annoyance due to aviation noise. This chapter presents and details, as simply as possible, the complex relationships between physical phenomena and noise perception in order to highlight the key notions in aviation noise issues. The readers will find answers to many usual and legitimate questions, for example what is the relationship between the perceived noise and the level of the physical noise related to the European ACARE goals which are expressed sometimes as EPNL reduction in dB or sometimes as perceived noise reduction in percent.
Perspective on 25 Years of European Aircraft Noise Reduction Technology Efforts and Shift Towards Global Research Aimed at Quieter Air Transport
Authors: Kors Eugene , Collin Dominique
Published: January 2022

This article provides a perspective on 25 years of European aircraft noise reduction technology efforts as well as the gradual shift towards a more global research effort aimed at quieter air transport activity. It covers the following aspects:

Introduction - Background and general context of noise from air transport operations

European context – ACARE Strategic Research Agendas and establishment of the 2020 and 2050 aviation environmental goals

Phased strategy towards 2020 targets and beyond

A coordinated European aviation noise research effort

Assessment of progress relative to ACARE noise reduction targets

Addressing the longer-term objectives – Noise and the ACARE SRIA

Community building

Lessons learned
The ‘Management’ of Migration – And of the Resulting Irregularities
Authors: Schweitzer Reinhard
Published: January 2022

This chapter lays out the conceptual and analytical frameworks for my analysis and embeds it in the existing literature on the internalisation of immigration control and the role of implementing actors and their everyday practices. It starts with a critical discussion of ‘migration management’ and the limits of state control over contemporary migration. After conceptualising contemporary migrant irregularity and what I call the micro-management of it, I develop the theoretical and conceptual framework of my study, which combines a critical understanding of internal bordering processes with Foucauldian conceptualisations of power and governmentality as well as crucial insights from organisation studies. At the end of the chapter I explain my analytical framework and its application in detail.
Conclusion
Authors: Schweitzer Reinhard
Published: January 2022

In the concluding chapter I summarise my findings and draw systematic comparisons across the three sectors of service provision and between the two field sites. I then discuss the immediate and wider implications of my findings and the usefulness of my approach and framework for future research.
Long-range fermions and critical dualities
Authors: Chai Noam , Chakraborty Soumangsu , Goykhman Mikhail , Sinha Ritam
Published: January 2022

Abstract

We construct long-range fermionic models with the Gross-Neveu and Gross­Neveu-Yukawa interaction, and argue that their critical regimes are equivalent. To this end, we calculate various CFT data in ϵ- and 1/N-expansion, and demonstrate their agreement in the overlapping regimes of validity.
Inconsistency of islands in theories with long-range gravity
Authors: Geng Hao , Karch Andreas , Perez-Pardavila Carlos , Raju Suvrat , Randall Lisa , Riojas Marcos , Shashi Sanjit
Published: January 2022

Abstract

In ordinary gravitational theories, any local bulk operator in an entanglement wedge is accompanied by a long-range gravitational dressing that extends to the asymptotic part of the wedge. Islands are the only known examples of entanglement wedges that are disconnected from the asymptotic region of spacetime. In this paper, we show that the lack of an asymptotic region in islands creates a potential puzzle that involves the gravitational Gauss law, independently of whether or not there is a non-gravitational bath. In a theory with long-range gravity, the energy of an excitation localized to the island can be detected from outside the island, in contradiction with the principle that operators in an entanglement wedge should commute with operators from its complement. In several known examples, we show that this tension is resolved because islands appear in conjunction with a massive graviton. We also derive some additional consistency conditions that must be obeyed by islands in decoupled systems. Our arguments suggest that islands might not constitute consistent entanglement wedges in standard theories of massless gravity where the Gauss law applies.
On the finite index subgroups of Houghton’s groups
Authors: Cox Charles Garnet
Published: January 2022

Houghton’s groups $$H_2, H_3, \ldots $$

H
2

,

H
3

,
…

are certain infinite permutation groups acting on a countably infinite set; they have been studied, among other things, for their finiteness properties. In this note we describe all of the finite index subgroups of each Houghton group, and their isomorphism types. Using the standard notation that d(G) denotes the minimal size of a generating set for G, we then show, for each $$n\in \{2, 3,\ldots \}$$

n
∈
{
2
,
3
,
…
}

and U of finite index in $$H_n$$

H
n

, that $$d(U)\in \{d(H_n), d(H_n)+1\}$$

d

(
U
)

∈
{
d

(

H
n

)

,
d

(

H
n

)

+
1
}

and characterise when each of these cases occurs.
Impfstoffe gegen Hepatitis E: Wo stehen wir?
Authors: Behrendt Patrick , Wedemeyer Heiner
Published: January 2022

In Europa ist aktuell kein Impfstoff gegen das Hepatitis-E-Virus (HEV) zugelassen. Demgegenüber steht in China bereits seit 10 Jahren mit HEV-239 (Hecolin®, Xiamen Innovax Biotech Co., Xiamen, China) ein Vakzin gegen den HEV-Genotyp 4 zur Verfügung. Herausforderungen für die Entwicklung von Impfstoffen ergeben sich v. a. aus den Unterschieden zwischen den Genotypen bezüglich Verbreitung, Übertragungswege und Risikogruppen. Weitere Hindernisse sind die Umhüllung von HEV im Blut durch Wirtsmembranen, die Replikation in verschiedenen Organen außerhalb der Leber sowie schwächere Immunantworten in vulnerablen Gruppen. In diesem Artikel wird der aktuelle Stand der verfügbaren und in fortgeschrittener präklinischer Evaluation befindlichen Vakzine gegen HEV mit Fokus auf Strategien der Impfstoffentwicklung dargestellt. Herausforderungen und Limitationen werden beschrieben.

Aktuelle Impfkandidaten fokussieren auf proteinbasierte Immunisierungen mit dem Ziel der Induktion von schützenden, neutralisierenden Antikörperantworten. Das Ziel der HEV-239-Zulassungsstudie mit mehr als 100.000 Studienteilnehmern war die Verhinderung von akuten symptomatischen Infektionen. Es ist jedoch unklar, inwieweit asymptomatische Infektionen durch das Vakzin verhindert wurden und ob es in Risikopatienten für einen komplizierten Verlauf, wie Patienten mit Leberzirrhose, Immunsupprimierten und Schwangeren, effektiv genug wirkt. Effiziente In-vitro-Modelle ermöglichen zunehmend die Entwicklung von monoklonalen neutralisierenden Antikörpern zur passiven Immunisierung oder Therapie.

Zukünftige Vakzine sollten neben einem sehr guten Sicherheitsprofil eine eindeutige Protektion gegenüber allen Genotypen demonstrieren. Die Entwicklung einer effizienten passiven Immunisierungsstrategie, insbesondere für immunsupprimierte Personen, ist wünschenswert.
Oblique decision tree induction by cross-entropy optimization based on the von Mises–Fisher distribution
Authors: Bollwein Ferdinand , Westphal Stephan
Published: January 2022

Oblique decision trees recursively divide the feature space by using splits based on linear combinations of attributes. Compared to their univariate counterparts, which only use a single attribute per split, they are often smaller and more accurate. A common approach to learn decision trees is by iteratively introducing splits on a training set in a top–down manner, yet determining a single optimal oblique split is in general computationally intractable. Therefore, one has to rely on heuristics to find near-optimal splits. In this paper, we adapt the cross-entropy optimization method to tackle this problem. The approach is motivated geometrically by the observation that equivalent oblique splits can be interpreted as connected regions on a unit hypersphere which are defined by the samples in the training data. In each iteration, the algorithm samples multiple candidate solutions from this hypersphere using the von Mises–Fisher distribution which is parameterized by a mean direction and a concentration parameter. These parameters are then updated based on the best performing samples such that when the algorithm terminates a high probability mass is assigned to a region of near-optimal solutions. Our experimental results show that the proposed method is well-suited for the induction of compact and accurate oblique decision trees in a small amount of time.
Maximizing the consistency between regional and global reference frames utilizing inheritance of seasonal displacement parameters
Authors: Gómez Demián D. , Bevis Michael G. , Caccamise Dana J.
Published: January 2022

Although modern global geometric reference frames (GRFs) such as the International Terrestrial Reference Frame (ITRF) can be used anywhere on Earth, regional reference frames (RRFs) are still used to densify geodetic control and optimize solutions for continental-scale areas and national purposes. Such RRFs can be formed by densifying the ITRF, utilizing GPS / GNSS stations common to both the ITRF and the RRF. It is possible to attach a RRF to a GRF by ensuring that some or all of the coefficients of the trajectory models in the RRF are ‘inherited’ from the trajectory models that define the GRF. This can be done on an epoch-by-epoch basis, or (our preference) via transformations that operate simultaneously in space and time. This paper documents inconsistencies in the densification of ITRF that arise when the common stations’ trajectory models ignore periodic displacements. This results in periodic coordinate biases in the RRF. We describe a generalized procedure to minimize this inconsistency when realizing any RRF aligned to the ITRF or any other ‘primary’ frame. We show the method used to realize the Argentine national frame Posiciones Geodésicas Argentinas (POSGAR) and discuss our results. Discrepancies in the periodic motion amplitudes in the vertical were reduced from 4 mm to less than 1 mm for multiple stations after applying our technique. We also propose adopting object-oriented programming terminology to describe the relationship between different reference frames, such as a regional and a global frame. This terminology assists in describing and understanding the hierarchy in geodetic reference frames.