Radiative Heat Transfer and Effective Transport Coefficients

The theory of heat transfer by electromagnetic radiation is based on the radiative transfer equation (RTE) for the radiation intensity, or equivalently on the Boltzmann transport equation (BTE) for the photon distribution. We focus in this review article, after a brief overview on different solution methods, on a recently introduced approach based on truncated moment expansion. Due to the linearity of the underlying BTE, the appropriate closure of the system of moment equations is entropy production rate minimization. This closure provides a distribution function and the associated effective transport coefficients, like mean absorption coefficients and the Eddington factor, for an arbitrary number of moments. The moment approach is finally illustrated with an application of the two-moment equations to an electrical arc

Taking Afrobarometer Data Everywhere

According to statistics gathered by research group Afrobarometer, many countries in Africa lack infrastructure and basic necessities. In fact, Afrobarometer knows the specific rates of need and availability sampled across thirty-six countries but more prosperous African countries do not know these numbers. These more developed countries are in a position to help their less fortunate neighbors if only made aware of the social and economic climate in the respective areas. Our partnership with Afrobarometer will allow us to advertise these statistics through the use of a mobile application. The data will be displayed in a way that is easy for the average reader to digest and understand. By exposing a larger African audience to the results from these public opinion surveys, Afrobarometer hopes to inspire these people to take action and make donations to the appropriate social benefit groups. The countries represented by the surveys can then receive help in the areas expressing need

Generating low-dimensional denoised representations of nonlinear data with superparamagnetic agents

Copyright ©2016 IEICEVisualisation of high-dimensional data by means of a low-dimensional embedding plays a key role in explorative data analysis. Classical approaches to dimensionality reduction, such as principal component analysis (PCA) and multidimensional scaling (MDS), struggle or even fail to reveal the relevant data characteristics when applied to noisy or nonlinear data structures. We present a novel approach for dimensionality reduction in combination with an automatic noise cleaning. By employing self-organising agents that are governed by the dynamics of the superparamagnetic clustering algorithm, the method is able to generate denoised low-dimensional embeddings for which the characteristics of nonlinear data structures are preserved or even emphasised. These properties are illustrated and compared to other approaches by means of toy and real-world examples

An Evaluation Schema for the Ethical Use of Autonomous Robotic Systems in Security Applications

We propose a multi-step evaluation schema designed to help procurement agencies and others to examine the ethical dimensions of autonomous systems to be applied in the security sector, including autonomous weapons systems

Who is controlling whom? Reframing “meaningful human control” of AI systems in security

Decisions in security contexts, including armed conflict, law enforcement, and disaster relief, often need to be taken under circumstances of limited information, stress, and time pressure. Since AI systems are capable of providing a certain amount of relief in such contexts, such systems will become increasingly important, be it as decision-support or decision-making systems. However, given that human life may be at stake in such situations, moral responsibility for such decisions should remain with humans. Hence the idea of “meaningful human control” of intelligent systems. In this opinion paper, we outline generic configurations of control of AI and we present an alternative to human control of AI, namely the inverse idea of having AI control humans, and we discuss the normative consequences of this alternative

Connexins in leukocytes: shuttling messages?

Gap junctions, formed by the connexin (Cx) protein family, are intercellular channels that permit the cytoplasmic exchange of ions and small metabolites between neighboring cells, a process called gap junction intercellular communication (GJIC). These channels possess unique properties, including distinctive permeabilities for various signaling molecules, which depend on the connexin member(s) that form them. Importantly, GJIC must be properly controlled as its misregulation might contribute to diseases. Morphological and functional studies have revealed ‘gap junction-like' structures and cell-to-cell communication involving cells of the immune system. The connexins involved in such contacts have been partially identified in recent years. This review focuses on the potential physiological roles of gap junctions in the development and recruitment of leukocytes as well as in the regulation of the immune response. Furthermore, the importance of GJIC in immuno-inflammatory pathologies is illustrated in atherosclerosi

MARLUI: Multi-Agent Reinforcement Learning for Adaptive UIs

Adaptive user interfaces (UIs) automatically change an interface to better support users' tasks. Recently, machine learning techniques have enabled the transition to more powerful and complex adaptive UIs. However, a core challenge for adaptive user interfaces is the reliance on high-quality user data that has to be collected offline for each task. We formulate UI adaptation as a multi-agent reinforcement learning problem to overcome this challenge. In our formulation, a user agent mimics a real user and learns to interact with a UI. Simultaneously, an interface agent learns UI adaptations to maximize the user agent's performance. The interface agent learns the task structure from the user agent's behavior and, based on that, can support the user agent in completing its task. Our method produces adaptation policies that are learned in simulation only and, therefore, does not need real user data. Our experiments show that learned policies generalize to real users and achieve on par performance with data-driven supervised learning baselines

Feasibility, acceptability and needs in telemedicine for palliative care.

BACKGROUND Telemedicine in palliative care was initially developed in countries where geography or resources limit access to care services. Recently, largely owing to the COVID-19 pandemic, this technology is being increasingly used in highly urbanised countries such as Switzerland. However, there is still scepticism regarding whether these tools can be used effectively in palliative care, a relationship-based speciality that is generally highly dependent on compassion, communication and direct human interaction. The objective of this review was to analyse the needs, elements of feasibility, and reasons for acceptance or possible barriers before the implementation of a telemedicine intervention in Switzerland. METHODS The method used was a scoping review, following the PRISMA-ScR reporting guidelines. We searched the PubMed, Ovid SP, Medline, Cochrane and Scopus databases for relevant reports. Charting and analyses of the data were done by a single researcher. A total of 520 records were screened and assessed for eligibility. Finally, 27 studies and 4 registry entries were included. Main reasons for exclusion were wrong population and intervention. RESULTS The prevailing study type was the single-arm intervention study. Most studies originated from countries with geographic barriers to access. Feasibility was good in 69% of all studies. Good acceptability (84.1-100%) was confirmed in the majority of the studies. The needs of the patients or the healthcare professionals were directly addressed in only five (16%) studies. Three needs were consistently reported: communication, coordination and technical reliability. CONCLUSION Despite a broad range of studies on telemedicine in palliative care, patients' needs are rarely addressed. Therefore, especially in countries such as Switzerland, a needs assessment is recommended before the implementation of a new telemedicine intervention, to guarantee high feasibility and acceptability