How 5G wireless (and concomitant technologies) will revolutionize healthcare?

The need to have equitable access to quality healthcare is enshrined in the United Nations (UN) Sustainable Development Goals (SDGs), which defines the developmental agenda of the UN for the next 15 years. In particular, the third SDG focuses on the need to “ensure healthy lives and promote well-being for all at all ages”. In this paper, we build the case that 5G wireless technology, along with concomitant emerging technologies (such as IoT, big data, artificial intelligence and machine learning), will transform global healthcare systems in the near future. Our optimism around 5G-enabled healthcare stems from a confluence of significant technical pushes that are already at play: apart from the availability of high-throughput low-latency wireless connectivity, other significant factors include the democratization of computing through cloud computing; the democratization of Artificial Intelligence (AI) and cognitive computing (e.g., IBM Watson); and the commoditization of data through crowdsourcing and digital exhaust. These technologies together can finally crack a dysfunctional healthcare system that has largely been impervious to technological innovations. We highlight the persistent deficiencies of the current healthcare system and then demonstrate how the 5G-enabled healthcare revolution can fix these deficiencies. We also highlight open technical research challenges, and potential pitfalls, that may hinder the development of such a 5G-enabled health revolution

Emotions and acceptance towards artificial intelligence and its evolution

Artificial Intelligence (AI) is one of the ultimate riddles of today’s generations and its applications are increasing day by day. Without realising, we deal with AI in the subtlest ways. Its rapid development has triggered several opinions among scientists, such as Elon Musk and Stephen Hawking, due to the controversial consequences it may imply. Apart from experts’ opinions, everyone belonging in society will be affected, whether positively or negatively. The present study aims to understand what kind of emotions are triggered by AI evolution, and if those emotions play a moderator role on the effect of AI acceptance on the agreement on which AI should evolve or not, with or without regulators. We ran a mixed methodology through a sample of 205 participants, applying an online survey, where we assessed the participants’ emotions regarding AI stimuli across three times, and further conducting a semi-structured interview. We concluded that, as opposite to what literature states, negative emotions tend to rise as the contact and knowledge regarding AI deepens. Symmetrically, non-negative emotions tend to decrease. Negative emotions seem to function as a moderator on the relationship between variables mentioned above. Also, the participants’ vision towards AI evolution seems to be hopeful, yet they recognise the need for regulators to be imperative.A Inteligência Artificial (IA) é um dos mais recentes e entusiasmantes enigmas da sociedade atual, e as suas aplicações aumentam de dia para dia. Sem nos apercebermos, lidamos com a IA nas formas mais subtis. O seu rápido desenvolvimento tem espoletado várias opiniões entre cientistas, tais como Elon Musk e Stephen Hawking, devido às consequências controversas que a IA poderá implicar. Além das opiniões dos especialistas, todos os que pertencem à sociedade irão ser afetados, quer positiva, quer negativamente. O presente estudo visa a compreender quais as emoções espoletadas pela evolução da IA, e se essas emoções tomam um papel moderador no efeito da aceitação da IA na concordância ou discordância com a sua evolução, com ou sem reguladores. Conduzimos um estudo com metodologia mista numa amostra de 205 participantes, aplicando um questionário online, onde avaliámos as emoções dos participantes relativamente aos estímulos apresentados em três tempos distintos. Posteriormente, realizámos uma entrevista semiestruturada. Concluímos que, em oposição ao que é encontrado na literatura, as emoções negativas tendem a aumentar, à medida que o conhecimento relativo à IA é aprofundado. Simetricamente, as emoções não-negativas tendem a diminuir. As emoções negativas parecem funcionar como moderadoras da relação entre as variáveis supramencionadas. Em adição, a visão dos participantes relativamente à evolução da IA parece ser favorável, no entanto, os participantes reconhecem a existência de reguladores como uma necessidade imperativa

Challenges and opportunities for quantifying roots and rhizosphere interactions through imaging and image analysis

The morphology of roots and root systems influences the efficiency by which plants acquire nutrients and water, anchor themselves and provide stability to the surrounding soil. Plant genotype and the biotic and abiotic environment significantly influence root morphology, growth and ultimately crop yield. The challenge for researchers interested in phenotyping root systems is, therefore, not just to measure roots and link their phenotype to the plant genotype, but also to understand how the growth of roots is influenced by their environment. This review discusses progress in quantifying root system parameters (e.g. in terms of size, shape and dynamics) using imaging and image analysis technologies and also discusses their potential for providing a better understanding of root:soil interactions. Significant progress has been made in image acquisition techniques, however trade-offs exist between sample throughput, sample size, image resolution and information gained. All of these factors impact on downstream image analysis processes. While there have been significant advances in computation power, limitations still exist in statistical processes involved in image analysis. Utilizing and combining different imaging systems, integrating measurements and image analysis where possible, and amalgamating data will allow researchers to gain a better understanding of root:soil interactions