This article looks again at the history of British migration policy in the 1940s and 1950s by centering international and imperial politics, and by drawing on archives related to shipping. These sources suggest that the British government sought to reactivate a system of race-segregated mobility across the Empire-Commonwealth after the Second World War. This involved subsidizing fares for emigrants bound for Australia, transporting migrants from Europe to the UK, and withdrawing shipping from routes that connected the Caribbean to the UK. Very soon, however, these policies came under strain. There were not enough deep-sea ships to meet demand for berths to Australia or to bring over recruited European migrants. Then the Australian government found new ways to ship migrants from continental Europe by signing a deal with the International Refugee Organization, challenging UK policy to keep Australian immigration British. Meanwhile, new routes were opened up from the Caribbean and South Asia to the UK. These trends raised a host of dilemmas for policymakers and all related to transport infrastructure. Thinking about transport can deepen our understanding of migration history, and the article's conclusion suggests some of the ways that taking such an approach can contribute to existing explanations for the government's fateful decision to amend the UK's nationality and citizenship legislation during the 1960s.

In light of the growing threat of climate change and urgency of mitigation at the societal and individual level, an exponentially growing body of research has addressed how and what people think about climate change—ranging from basic judgments of truth and attitudes about risk to predictions of future outcomes. However, the field is also beset by a striking variety of items and scales used to measure climate change beliefs, with notable differences in content, untested structural assumptions, and unsatisfactory or unknown psychometric properties. In a series of four studies (total N = 2,678), scales for the assessment of climate change beliefs are developed that are comprehensive and balanced in content and psychometrically sound. The latent construct structure is tested, and evidence of high rank-order stability (1-year retest-reliability) and predictive validity (for policy preferences and actual behavior) provided.

Advancements in wearable robots aim to improve user motion, motor control, and overall experience by minimizing energetic cost (EC). However, EC is challenging to measure and it is typically indirectly estimated through respiratory gas analysis. This study introduces a novel EMG-based objective function that captures individuals’ natural energetic expenditure during walking. The objective function combines information from electromyography (EMG) variables such as intensity and muscle synergies. First, we demonstrate the similarity of the proposed objective function, calculated offline, to the EC during walking. Second, we minimize and validate the EMG-based objective function using an online Bayesian optimization algorithm. The walking step frequency is chosen as the parameter to optimize in both offline and online approaches in order to simplify experiments and facilitate comparisons with related research. Compared to existing studies that use EC as the objective function, results demonstrated that the optimization of the presented objective function reduced the number of iterations and, when compared with gradient descent optimization strategies, also reduced convergence time. Moreover, the algorithm effectively converges toward an optimal step frequency near the user’s preferred frequency, positively influencing EC reduction. The good correlation between the estimated objective function and measured EC highlights its consistency and reliability. Thus, the proposed objective function could potentially optimize lower limb exoskeleton assistance and improve user performance and human–robot interaction without the need for challenging respiratory gas measurements.

Antenna arrays are a main driver of next generation millimeter-wave communication and radar systems as shrinking antenna sizes leverage larger arrays to compensate for reduced link budget. However, conventional phase controlled arrays exhibit a frequency dependent scan angle that appears as loss to a fixed counterpart. Bandwidth limitations introduced by the so-called beam squint effect hinder larger array sizes and data rates thereby generating a demand for timed arrays as a solution. This paper gives a quantified overview of the beam squint phenomenon, different hardware architectures as well as evaluation parameters and common shortcomings of true-time delay (TTD) elements. A broad variety of TTD realizations from literature are compared by their operational principles and performance. Finally, the delay interpolation principle, its non-idealities, and their impact on a hierarchically time delay controlled D-band antenna array are described. Extended content on a previously published, continuously tunable TTD implementation at a center frequency of 144 GHz with a bandwidth of 26 GHz and a delay range of 1.75 ps that requires only 0.53 × 0.3 mm2 of core chip area is presented. Measurement results have been obtained from a demonstrator manufactured in 130 nm BiCMOS technology.

This manuscript showcases the latest advancements in deepImageJ, a pivotal Fiji/ImageJ plugin for bioimage analysis in life sciences. The plugin, known for its user-friendly interface, facilitates the application of diverse pre-trained convolutional neural networks to custom data. The manuscript demonstrates several deepImageJ capabilities, particularly in deploying complex pipelines, three-dimensional (3D) image analysis, and processing large images. A key development is the integration of the Java Deep Learning Library, expanding deepImageJ’s compatibility with various deep learning (DL) frameworks, including TensorFlow, PyTorch, and ONNX. This allows for running multiple engines within a single Fiji/ImageJ instance, streamlining complex bioimage analysis workflows. The manuscript details three case studies to demonstrate these capabilities. The first case study explores integrated image-to-image translation followed by nuclei segmentation. The second case study focuses on 3D nuclei segmentation. The third case study showcases large image volume segmentation and compatibility with the BioImage Model Zoo. These use cases underscore deepImageJ’s versatility and power to make advanced DLmore accessible and efficient for bioimage analysis. The new developments within deepImageJ seek to provide a more flexible and enriched user-friendly framework to enable next-generation image processing in life science.

Consider a flow in $\mathbb{R}^3$ and let K be the biggest invariant subset of some compact region of interest $N \subseteq \mathbb{R}^3$. The set K is often not computable, but the way the flow crosses the boundary of N can provide indirect information about it. For example, classical tools such as Ważewski’s principle or the Poincaré–Hopf theorem can be used to detect whether K is non-empty or contains rest points, respectively. We present a criterion that can establish whether K has a non-trivial homology by looking at the subset of the boundary of N along which the flow is tangent to N. We prove that the criterion is as sharp as possible with the information it uses as an input. We also show that it is algorithmically checkable.

This paperpresents the measurement procedure as well as the calculations and theoretical background for the estimation of particle sizes with the help of a dual-frequency measurement setup. For the measurement, two fully integrated radar sensors are implemented which offer advantages over typically used technologies at high frequencies. The first sensor has a constant transmitting frequency of 90 GHz while the second sensor offers a possibility to vary the transmitting frequency over the entire D-band with frequencies between 110 and 180 GHz. With these frequencies, different sizes can be determined. The presented approach makes use of the different transitions between the linear increasing Rayleigh scattering regime and the Mie regime. With a fitting indoor measurement setup that resembles an industrial duct, the approach is verified for spheroid glass particles with a diameter of 0.875 mm. The results show a slight deviation from the expected value of particle sizes overall.

The agency of a person with young onset dementia (YOD) changes owing to individual symptoms, uncertainty about the speed of progression and the severity of YOD. Dementia usually greatly interrupts life and reduces agency. Previous studies show that some people and families integrate and cope with dementia better than others. This study aimed to find out how YOD changes the agency of the person who has it and what family members’ role is in forming their agency. The data were collected in Finland in semi-structured interviews with 14 people with YOD and 15 family members, about a year after the diagnosis. These two data sets were analysed with a narrative method, actantial analysis. A wide variety of elements, both human and non-human factors, were found to promote and undermine agency. It was found that people with YOD need both integrity and flexibility to reconstruct their own agency. Resources support them in this process of reconstruction, and hinderers interrupt the process. This combination of integrity and flexibility, resources and hinderers, generates how people with YOD recount the future, the aims they set and how they reconstruct their agency. Other people, especially family members, are part of this dynamic process and when their relationship is cohesive, the agency of both parties increases. The participants used ideal and burdensome storylines to narrate factors that supported or interrupted their agency. Based on our findings, narrating one’s situation is, for coping, not only a means but its very basis.

This study uses a rational choice approach to argue that an under-theorized and rarely tested cause of governmental discrimination against religious minorities is its popularity. Specifically, we argue that self-interested politicians are more likely to enact discriminatory policies when they believe said discrimination will be popular. These policies, in turn, have payoffs via increased public perceptions of governmental legitimacy. Using the Religion and State project, round 3 and World Values Survey data for members of the majority religion between 1990 and 2014 in 58 Christian-majority countries, we demonstrate that prejudice against members of other religions predicts increased governmental religious discrimination, which is, in turn, associated with higher confidence in government, legislatures, and political parties. While our results are specific to discrimination against religious minorities, this suggests that when discrimination against minorities in general is popular, politicians are likely to oblige.

Biodiversity shortfalls and taxonomic bias can lead to inaccurate assessment of conservation priorities. Previous literature has begun to explore practical reasons why some species are discovered sooner or are better researched than others. However, the deeper socio-cultural causes for undiscovered and neglected biodiversity, and the value of collectively analysing species at risk of unrecorded, or “dark”, extinction, are yet to be fully examined. Here, we argue that a new label (we propose “shadow diversity”) is needed to shift our perspective from biodiversity shortfalls to living, albeit unknown, species. We suggest this linguistic shift imparts intrinsic value to these species, beyond scientific gaze and cultural systems. We review research on undiscovered, undetected and hidden biodiversity in the fields of conservation biology, macroecology and genetics. Drawing on philosophy, geography, history and sociology, we demonstrate that a range of socio-cultural factors (funding, education and historical bias) combine with traditional, practical impediments to limit species discovery and detection. We propose using a spectrum of shadow diversity which enables a complex, non-binary and comprehensive approach to biodiversity unknowns. Shadow diversity holds exciting potential as a tool to increase awareness, appreciation and support for the conservation of traditionally less studied wildlife species and sites, from soil microbes to less charismatic habitat fragments. We advocate for a shift in how the conservation community and wider public see biodiversity and an increase in popular support for conserving a wider range of life forms. Most importantly, shadow diversity provides appropriate language and conceptual frameworks to discuss species absent from conservation assessment and at potential risk of dark extinction.

We present a new proof of the compactness of bilinear paraproducts with CMO symbols. By drawing an analogy to compact linear operators, we first explore further properties of compact bilinear operators on Banach spaces and present examples. We then prove compactness of bilinear paraproducts with CMO symbols by combining one of the properties of compact bilinear operators thus obtained with vanishing Carleson measure estimates and interpolation of bilinear compactness.

Language variation is demonstrably affected by accumulated experiences reflecting the consequences of the contexts in which words are most frequently used. Yet, these contextual frequency effects are seldom explored in children’s speech. This study uses a corpus-based approach to investigate how 29 Spanish-speaking children, aged 5–15, realize word-initial Spanish /d/ as a function of accumulated experiences with /d/-initial words in articulatory contexts that promote reduction. Contextual frequency effects are also examined in 12 Spanish-speaking adults from the children’s community. Cumulative experience is estimated as the form’s frequency of occurrence in a specific context that promotes a specific variant. Results reveal contextual frequency effects in both the child and adult data. Moreover, the extent of the contextual frequency effect is comparable across generations.

Cartels today are illegal and illegitimate across the globe. Yet until the end of World War II, cartels were legal, ubiquitous, and popular—especially in Europe. How, then, did cartels become bad, if they had been considered a positive force for capitalist stabilization and peace in the first half of the 20th century? That is the question this dissertation poses. By the 1930s, over 1,000 monopolistic agreements regulated nearly half of world trade. International cartels governed the interwar world economy, setting prices and output quotas, dividing world markets, regulating trade flows, and even controlling the transfer of patents across firms and sovereign state borders. I conceptualize this regime as “cartel capitalism.” Most cartels were headquartered in industrial Europe. First, I trace how a surprising consensus in interwar Europe—comprising national governments; international organizations like the League of Nations; industrialists, led by the International Chamber of Commerce; federalists; and even socialists—backed cartels as a panacea to the problems of reconstruction after 1918, namely the quest for peace and stable markets. However, in the wake of 1945, most countries in Western Europe—along with the new supranational European Coal and Steel Community (ECSC, 1951) and European Economic Community (EEC)—started prohibiting cartels. My project illuminates the causes and consequences of this great reversal. Monopoly Menace reveals, for the first time, how Europe’s transnational reckoning with the shocks of the Great Depression, fascism, and total war produced a genuine anticartel revolution that rewrote the rules of the modern European and global economy. Monopoly Menace ends by illuminating how American, British, French, and West German postwar planners designed new national welfare states, the Bretton Woods Order, and the European Union on the neglected foundation of anti-cartel policies.

To make profitable investment decisions, investors must know and understand their risks. They can learn about these risks in different ways. Evidence suggests that investors who learn from a ‘risk tool’ simulator perceive financial risk more accurately, feel more informed and confident, and thus take on more financial risk. We attempt a conceptual replication of these findings, exploring whether they extend from kind to wicked environments and to investors with some investment experience. We conducted four studies online, amounting to 3,804 participants, and observe that neither the risk tool nor any of the other risk communication interventions lead to different risk taking or to different subjective representations of risk relative to a control condition in which participants received no intervention. We evaluated several moderators, but none could explain the absence of an intervention effect, suggesting that the effect of risk tools and other interventions could be limited.