Terrestrial Planet Optical Phase Curves. I. Direct Measurements of the Earth

NASA’s EPOXI mission used the Deep Impact spacecraft to observe the disk-integrated Earth as an analog to terrestial exoplanets’ appearance. The mission took five 24 hr observations in 2008–2009 at various phase angles (57.°7–86.°4) and ranges (0.11–0.34 au), of which three equatorial (E1, E4, E5) and two polar (P1, North and P2, South). The visible data taken by the HRIV instrument ranges from 0.3 to 1.0 μm, taken trough seven spectral filters that have spectral widths of about 100 nm, and which are centered about 100 nm apart, from 350 to 950 nm. The disk-integrated, 24 hr averaged signal is used in a phase angle analysis. A Lambertian-reflecting, spherical planet model is used to estimate geometric albedo for every observation and wavelength. The geometric albedos range from 0.143 (E1, 950 nm) to 0.353 (P2, 350 nm) and show wavelength dependence. The equatorial observations have similar values, while the polar observations have higher values due to the ice in view. Therefore, equatorial observations can be predicted for other phase angles, but (Earth-like) polar views (with ice) would be underestimated.

Deep impact? Is mercury in dab (Limanda limanda) a marker for dumped munition? Results from munition dump site Kolberger Heide (Baltic Sea)

Dumped munitions contain various harmful substances which can affect marine biota like fish. One of them is mercury (Hg), included in the common explosive primer Hg fulminate. There is still a lack of knowledge whether dumped munitions impact the Hg concentrations in the Baltic Sea environment. This study aims to answer the question if dab caught at the dump site Kolberger Heide show higher Hg concentrations released from munition sources and whether Hg in fish is a usable marker for munition exposure. Therefore, a total of 251 individual dab (Limanda limanda) were analysed including 99 fish from the dump site. In fish from the Kolberger Heide, no elevated Hg concentrations were found compared to reference sites when age-dependent bioaccumulation of mercury was considered. Therefore we conclude that Hg in fish is no suitable indicator for exposure to munition dumping, e.g. in the frame of possible future monitoring studies as Hg exposure originating from dumped munition is only a small contributor to overall Hg exposure of fish.

Meta-Learning for Few-Shot Plant Disease Detection

Plant diseases can harm crop growth, and the crop production has a deep impact on food. Although the existing works adopt Convolutional Neural Networks (CNNs) to detect plant diseases such as Apple Scab and Squash Powdery mildew, those methods have limitations as they rely on a large amount of manually labeled data. Collecting enough labeled data is not often the case in practice because: plant pathogens are variable and farm environments make collecting data difficulty. Methods based on deep learning suffer from low accuracy and confidence when facing few-shot samples. In this paper, we propose local feature matching conditional neural adaptive processes (LFM-CNAPS) based on meta-learning that aims at detecting plant diseases of unseen categories with only a few annotated examples, and visualize input regions that are ‘important’ for predictions. To train our network, we contribute Miniplantdisease-Dataset that contains 26 plant species and 60 plant diseases. Comprehensive experiments demonstrate that our proposed LFM-CNAPS method outperforms the existing methods.

Changes in Mathematics Core Curriculum and Matriculation Exam in the Light of the COVID-19-Shock

The new National Core Curriculum came into force in September 2020 in Hungarian schools. The COVID-19 pandemic has had a deep impact on the final stages of its development. In this paper we have selected two areas for analysis: the fundamental principles of mathematics curriculum and the matriculation exam in mathematics. We propose improvements in both fields, further emphasizing the importance of skills in displaying, understanding and processing information, including visual information obtained as a source or outcome of a problem. We argue that representation, interpretation, and critical evaluation of data and information must be essential parts of the mathematics curriculum. In this context, we also propose a new type of task for the matriculation exam: a complex essay task. The ultimate goal is the development of cross-cutting competencies to support students to become citizens who can make responsible decisions based on the data and knowledge available.

Nostalgia in the Novel (ALWAN and AFSANE) by Mamosta Jaafar

Nostalgia for the past is a phenomenon that is present in most members of society, but its impact varies from one person to another, and nostalgia appears in humans in cases of distance and alienation from the homeland, in other words when a person is uprooted from his roots and spends his life in the diaspora, and here nostalgia for the past dominates his thinking and reflections . And nostalgia leaves a deep impact on the author. That is why the book resorts to the world of writing to get rid of the pain of alienation. And back again to the world of childhood. With this hope, they can interrupt for a moment from the present time and return to the time of youth. Here, they can make a magical trip to the past in order to give their souls and themselves a moment of calm and stability. In this research, we have tried to embody the types of nostalgia in the novel (ALWAN and AFSANE).

Impact of COVID-19 pandemic on enterprises in Italy

The Covid-19 pandemic and the measures that have been adopted to try and contain it have had a deep impact on the Italian economy, the scope of which cannot be perfectly gauged as yet. The consequences of Covid-19 crisis have affected Italian enterprises’ operating in different sectors. Most of enterprises have been obliged to change their technical ways. Thus, new specific trends and actions have been adopted during this challenging period.

Italian Twitter semantic network during the Covid-19 epidemic

The Covid-19 pandemic has had a deep impact on the lives of the entire world population, inducing a participated societal debate. As in other contexts, the debate has been the subject of several d/misinformation campaigns; in a quite unprecedented fashion, however, the presence of false information has seriously put at risk the public health. In this sense, detecting the presence of malicious narratives and identifying the kinds of users that are more prone to spread them represent the first step to limit the persistence of the former ones. In the present paper we analyse the semantic network observed on Twitter during the first Italian lockdown (induced by the hashtags contained in approximately 1.5 millions tweets published between the 23rd of March 2020 and the 23rd of April 2020) and study the extent to which various discursive communities are exposed to d/misinformation arguments. As observed in other studies, the recovered discursive communities largely overlap with traditional political parties, even if the debated topics concern different facets of the management of the pandemic. Although the themes directly related to d/misinformation are a minority of those discussed within our semantic networks, their popularity is unevenly distributed among the various discursive communities.

Synthesis with Mandatory Stop Actions

We study the impact of the need for the agent to obligatorily instruct the action stop in her strategies. More specifically we consider synthesis (i.e., planning) for LTLf goals under LTL environment specifications in the case the agent must mandatorily stop at a certain point. We show that this obligation makes it impossible to exploit the liveness part of the LTL environment specifications to achieve her goal, effectively reducing the environment specifications to their safety part only. This has a deep impact on the efficiency of solving the synthesis, which can sidestep handling Buchi determinization associated to LTL synthesis, in favor of finite-state automata manipulation as in LTLf synthesis. Next, we add to the agent goal, expressed in LTLf, a safety goal, expressed in LTL. Safety goals must hold forever, even when the agent stops, since the environment can still continue its evolution. Hence the agent, before stopping, must ensure that her safety goal will be maintained even after she stops. To do synthesis in this case, we devise an effective approach that mixes a synthesis technique based on finite-state automata (as in the case of LTLf goals) and model-checking of nondeterministic Buchi automata. In this way, again, we sidestep Buchi automata determinization, hence getting a synthesis technique that is intrinsically simpler than standard LTL synthesis.

Segregation, Inequalities and Discrimination

The aim of this paper is to show that school segregation not only has an impact on school achievement, but also on more qualitative issues such as the perception of inequalities and the feeling of discrimination. I propose an explanation for why the feeling of being trapped in segregated, ‘disreputable’ public schools, a feeling which is shared among people from disadvantaged and immigrant backgrounds, as well as parts of the lower-middle class, has a deep impact on social cohesion. We will see how this encourages working-class people to think more in terms of discrimination (segregation as the result of an intentional process) rather than in terms of inequality, calling into question public schools’ capacity for guaranteeing equal opportunity. This is another way of analyzing how people facing an unequal context perceive injustice.

The Contribution of Experimental Energy Facilities to the Achievement of SDG in their Environment: The Case of IFMIF-DONES

Scientific infrastructures are known to have a deep impact from two main perspectives: the finality they were designed to, and other collateral impacts like changes in the economic geographic land where they are settled. However, the effects from other perspectives like social evolution and contribution to Sustainable Development have not been studied in depth yet. In this work, the effects of the implementation of the "International Fusion Materials Irradiation Facility – Demo Oriented NEutron Source" (IFMIF-DONES) in a rural area in the Southern Spain will be discussed.