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Background:
Brain lesions in language-related cortical areas remain a challenge in the clinical routine. In recent years the resting-state fMRI (rs-fMRI) was shown to be a feasible method for preoperative language assessment. The aim of this study was to examine whether language-related resting-state components, which have been obtained using a data-driven independent-component-based identification algorithm, can be supportive in determining language dominance in the left or right hemisphere.
Methods:
Twenty patients suffering from brain lesions close to supposed language relevant cortical areas were included. Rs-fMRI and task-based (tb-fMRI) were performed for the purpose of preoperative language assessment. Tb-fMRI included a verb generation task with an appropriate control condition (a syllable switching task) to decompose language critical and language supportive processes. Subsequently, the best fitting ICA component for the resting-state language network (RSLN) referential to general linear models (GLMs) of the tb-fMRI (including models with and without linguistic control conditions) was identified using an algorithm based on the Dice-index.
Results:
The RSLNs associated with GLMs using a linguistic control condition led to significantly higher laterality indices than GLM baseline contrasts. LIs derived from GLM contrasts with and without control conditions alone did not differ significantly.
Conclusion:
In general, the results suggest that determining language dominance in the human brain is feasible both with tb-fMRI and rs-fMRI, and in particular, the combination of both approaches yields a higher specificity in preoperative language assessment. Moreover, we can conclude that the choice of the language mapping paradigm is crucial for the mentioned benefits.
Brain lesions in language-related cortical areas remain a challenge in the clinical routine. In recent years, the resting-state fMRI (RS-fMRI) was shown to be a feasible method for preoperative language assessment. The aim of this study was to examine whether language-related resting-state components, which have been obtained using a data-driven independent-component-based identification algorithm, can be supportive in determining language dominance in the left or right hemisphere. Twenty patients suffering from brain lesions close to supposed language-relevant cortical areas were included. RS-fMRI and task-based (TB-fMRI) were performed for the purpose of preoperative language assessment. TB-fMRI included a verb generation task with an appropriate control condition (a syllable switching task) to decompose language-critical and language-supportive processes. Subsequently, the best fitting ICA component for the resting-state language network (RSLN) referential to general linear models (GLMs) of the TB-fMRI (including models with and without linguistic control conditions) was identified using an algorithm based on the Dice index. Thereby, the RSLNs associated with GLMs using a linguistic control condition led to significantly higher laterality indices than GLM baseline contrasts. LIs derived from GLM contrasts with and without control conditions alone did not differ significantly. In general, the results suggest that determining language dominance in the human brain is feasible both with TB-fMRI and RS-fMRI, and in particular, the combination of both approaches yields a higher specificity in preoperative language assessment. Moreover, we can conclude that the choice of the language mapping paradigm is crucial for the mentioned benefits.
COVID-19 and the ageing workforce: global perspectives on needs and solutions across 15 countries
(2021)
BACKGROUND: COVID-19 has a direct impact on the employment of older people. This adds to the challenge of ageism. The World Health Organization has started a worldwide campaign to combat ageism and has called for more research and evidence-based strategies that have the potential to be scaled up. This study specifically aims to identify solutions to combat the adverse effects of COVID-19 on the global ageing workforce.
METHODS: We present 15 case studies from different countries and report on what those countries are doing or not doing to address the impact of COVID-19 on ageing workers.
RESULTS: We provide examples of how COVID-19 influences older people's ability to work and stay healthy, and offer case studies of what governments, organizations or individuals can do to help ensure older people can obtain, maintain and, potentially, expand their current work. Case studies come from Australia, Austria, Canada, China, Germany, Israel, Japan, Nigeria, Romania, Singapore, Sweden, South Korea, Thailand, United Kingdom (UK), and the United States (US). Across the countries, the impact of COVID-19 on older workers is shown as widening inequalities. A particular challenge has arisen because of a large proportion of older people, often with limited education and working in the informal sector within rural areas, e.g. in Nigeria, Thailand and China. Remedies to the particular disadvantage experienced by older workers in the context of COVID are presented. These range from funding support to encouraging business continuity, innovative product and service developments, community action, new business models and localized, national and international actions. The case studies can be seen as frequently fitting within strategies that have been proven to work in reducing ageism within the workplace. They include policy and laws that have increased benefits to workers during lockdowns (most countries); educational activities such as coaching seniorpreneurship (e,g, Australia); intergenerational contact interventions such as younger Thai people who moved back to rural areas and sharing their digital knowledge with older people and where older people reciprocate by teaching the younger people farming knowledge.
CONCLUSION: Global sharing of this knowledge among international, national and local governments and organizations, businesses, policy makers and health and human resources experts will further understanding of the issues that are faced by older workers. This will facilitate the replication or scalability of solutions as called for in the WHO call to combat ageism in 2021. We suggest that policy makers, business owners, researchers and international organisations build on the case studies by investing in evidence-based strategies to create inclusive workplaces. Such action will thus help to challenge ageism, reduce inequity, improve business continuity and add to the quality of life of older workers.
Quantum computing promises to overcome computational limitations with better and faster solutions for optimization, simulation, and machine learning problems. Europe and Germany are in the process of successfully establishing research and funding programs with the objective to dvance the technology’s ecosystem and industrialization, thereby ensuring digital sovereignty, security, and competitiveness. Such an ecosystem comprises hardware/software solution providers, system integrators, and users from research institutions, start-ups, and industry. The vision of the Quantum Technology and Application Consortium (QUTAC) is to establish and advance the quantum computing ecosystem, supporting the ambitious goals of the German government and various research programs. QUTAC is comprised of ten members representing different industries, in particular automotive manufacturing, chemical and pharmaceutical production, insurance, and technology. In this paper, we survey the current state of quantum computing in these sectors as well as the aerospace industry and identify the contributions of QUTAC to the ecosystem. We propose an application-centric approach for the industrialization of the technology based on proven business impact. This paper identifies 24 different use cases. By formalizing high-value use cases into well-described reference problems and benchmarks, we will guide technological progress and eventually commercialization. Our results will be beneficial to all ecosystem participants, including suppliers, system integrators, software developers, users, policymakers, funding program managers, and investors.
The SMOOTH-robot is a mobile robot that-due to its modularity-combines a relatively low price with the possibility to be used for a large variety of tasks in a wide range of domains. In this article, we demonstrate the potential of the SMOOTH-robot through three use cases, two of which were performed in elderly care homes. The robot is designed so that it can either make itself ready or be quickly changed by staff to perform different tasks. We carefully considered important design parameters such as the appearance, intended and unintended interactions with users, and the technical complexity, in order to achieve high acceptability and a sufficient degree of utilization of the robot. Three demonstrated use cases indicate that such a robot could contribute to an improved work environment, having the potential to free resources of care staff which could be allocated to actual care-giving tasks. Moreover, the SMOOTH-robot can be used in many other domains, as we will also exemplify in this article.
The smooth transition between stable, Talbot-effect-dominated and modulationally unstable nonlinear optical beam propagation is described as the superposition of oscillating, growing and decaying eigenmodes of the common linearized theory of modulation instability. The saturation of the instability in form of breather maxima is embedded between eigenmode growth and decay. This explains well the changes of beam characteristics when the input intensity increases in experiments on modulation instability and breather excitation in spatial-spatial experimental platforms. An increased accuracy of instability gain measurements, a variety of interesting nonlinear beam scenarios and a more selective and well-directed breather excitation are demonstrated experimentally.
One of the fundamental challenges in L-PBF of filigree geometries, such as aortic stents used in biomedical applications, is the requirement for a robust yet easily removable support structure that allows each component to be successfully fabricated without distortion. To solve this challenge, an integrative experimental approach was attempted in the present study by identifying an optimal support structure design and an optimized support removal strategy for this design. The specimens were manufactured using four different support structure designs based on the geometry exposed to the laser beam during the L-PBF. Support removal procedures included sand blasting (SB), glass bead blasting (GB), and electrochemical polishing (ECP). The two best-performing designs (line and cross) were chosen due to shorter lead times and lower material consumption. As an additional factor that indicates a stable design, the breaking load requirement to remove the support structures was determined. A modified line support with a 145° included angle was shown to be the best support structure design in terms of breaking load, material consumption, and manufacturing time. All three procedures were used to ensure residue-free support removal for this modified line support design, with ECP proving to be the most effective.
Avoiding ice accumulation on aerodynamic components is of enormous importance to flight safety. Novel approaches utilizing surface dielectric barrier discharges (SDBDs) are expected to be more efficient and effective than conventional solutions for preventing ice accretion on aerodynamic components. In this work, the realization of SDBDs based on thin-film substrates by means of micro-electro-mechanical-systems (MEMS) technology is presented. The anti-icing performance of the MEMS SDBDs is presented and compared to SDBDs manufactured by printed circuit board (PCB) technology. It was observed that the 35 mu m thick electrodes of the PCB SDBDs favor surface icing with an initial accumulation of supercooled water droplets at the electrode impact edges. This effect was not observed for 0.3 mu m thick MEMS-fabricated electrodes indicating a clear advantage for MEMS-technology SDBDs for anti-icing applications. Titanium was identified as the most suitable material for MEMS electrodes. In addition, an optimization of the MEMS-SDBDs with respect to the dielectric materials as well as SDBD design is discussed.
A surface relief grating with a period of 30 mu m is embossed onto the surface of magnetoactive elastomer (MAE) samples in the presence of a moderate magnetic field of about 180 mT. The grating, which is represented as a set of parallel stripes with two different amplitude reflectivity coefficients, is detected via diffraction of a laser beam in the reflection configuration. Due to the magnetic-field-induced plasticity effect, the grating persists on the MAE surface for at least 90 h if the magnetic field remains present. When the magnetic field is removed, the diffraction efficiency vanishes in a few minutes. The described effect is much more pronounced in MAE samples with larger content of iron filler (80 wt%) than in the samples with lower content of iron filler (70 wt%). A simple theoretical model is proposed to describe the observed dependence of the diffraction efficiency on the applied magnetic field. Possible applications of MAEs as magnetically reconfigurable diffractive optical elements are discussed. It is proposed that the described experimental method can be used as a convenient tool for investigations of the dynamics of magnetically induced plasticity of MAEs on the micrometer scale.