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Towards an EU climate governance framework to deliver on the European Green Deal: policy options paper
Get PDFThe EU and its member states face the challenge of accelerating the transition to climate neutrality and negative greenhouse gas (GHG) emissions in increasingly turbulent times. But the
challenge of governing the climate and energy transition goes far beyond phasing out GHG emissions. Given the urgency, dynamism, complexity, contentiousness, and long-term, cross-cutting
nature of the “super wicked” climate challenge, the governance of the climate transition requires
sustained, comprehensive, and integrated efforts across all relevant policy fields and the whole
of society. To this end, the EU needs to devise political processes, structures and institutions
that empower democratic political systems in Europe to effectively respond to the climate challenge (hereinafter referred to as the EU’s “climate governance framework”).
In this paper, we identify key options for enhancing the EU’s evolving climate governance framework to this end. Building on the latest scientific knowledge of relevant best practice in Europe
and elsewhere, as for example reflected and acknowledged in the Intergovernmental Panel on
Climate Change’s Sixth Assessment Report (IPCC, 2022b), we review the EU’s existing climate
governance framework and identify EU-level policy options for further enhancing it across the
Union and its member states, while paying particular attention to key interactions, synergies. and tensions between individual governance elements
A versatile monitoring technique for real-time protein activity tracking within cellular and biomimetic scaffold environments
Get PDFHigh biological noise is intrinsic within biological systems, and this poses critical challenges
to the in-situ detection and measurement of biomolecular and protein activities important to
advancing approaches to disease and injury treatment. These challenges arise due to possible
non-specific binding of other molecules in the analyte’s surrounding medium. Currently the
techniques available to characterize protein behaviours in living biological systems are highly
elaborate and are generally greatly hindered by the high background noise. Here we present a
versatile and straight forward technique for monitoring proteins and protein interactions within
cells and other complex environments, based on a novel nano-bio-technology method. Highly
sensitive gold edge coated triangular silver nanoplates (AuTSNP), which are highly responsive
to molecular interactions on their surfaces, are used to probe protein behaviours within complex
cellular and tissue regeneration environments, as well as recognize antibody-antigen (Ab-Ag)
interactions within dynamic biological surroundings. The extracellular domains within tissues
involve macromolecules vital for the provision of structural support to surrounding cells and
signalling cues for the modulation of diverse cellular processes. Tissue scaffolds are designed
to mimic the extracellular architecture and functions. In this work, monitoring of the dynamic
behaviour of a critical extracellular protein, Fibronectin (Fn), within the presence of bone tissue
regeneration scaffolds and living cells is reported. The optical response of Fn functionalised
AuTSNP, is used to distinguish between compact and extended conformations of the protein
and indicating Fn unfolding and fibril formation on incubation within cells.
Moreover, successful detection of native Fn present in isolated Extracellular Matrix (ECM) by
using Anti-Fn antibody functionalised AuTSNP is performed. The excellent sensitivity and
straight forward application within complex cellular environments, poses AuTSNP as powerful
new tools to detect protein interactions and monitor essential protein activity. For this reason,
a potential COVID-19 detection platform is explored where SARS-CoV-2 Spike protein is
detected through a nanoplate-based system using its corresponding antibody, Anti-Spike. This
work is conducted within the presence of horse serum (HS) as complex environment where the
dynamic surroundings present a challenge for the straightforward detection of the Ab-Ag
complex binding, nonetheless, the research presented is a significant step towards the
development of new technologies for medical diagnosis and monitoringye
Granule-based material extrusion is comparable to filament-based material extrusion in terms of mechanical performances of printed PLA parts: a comprehensive investigation
Get PDFTo implement a circular economic life for thermoplastic waste, such as polylactic acid (PLA) waste from filament-based material extrusion (FME) printing and reduce the costs associated with producing filaments for the FME process, a granule-based material extrusion (GME) printer was developed by modifying a filament-based extrusion head with a granule-based extrusion head. However, concerns have been raised about the mechanical performance of parts printed using the GME method. Previous studies have reported mixed results, with some finding inferior mechanical performance of GME printed parts compared to FME counterparts, while others reported comparable or slightly better performance. Moreover, these studies were limited to tensile or flexural performance evaluations, lacked a clear explanation to support them. Therefore, to address this uncertainty and research gaps, a comprehensive mechanical performance comparison and analysis study was conducted among the specimens printed by these two types of material extrusion printers. Characterization tests were conducted, including tensile tests, impact tests, 3-point bending tests, and hardness tests, to reveal the comprehensive mechanical properties of the printed parts. Furthermore, scanning electron microscope (SEM) tests, differential scanning calorimetry (DSC) tests, thermal imaging, rheological tests, and gel permeation chromatography (GPC) tests were carried out to analyze and explain the results. The results indicated no significant differences (P > 0.05) in the mechanical properties of FME and GME printed parts in terms of tensile properties, flexural strength and modulus, and impact strength. However, there was a significant difference in shore D hardness and bending strain at break between the two methods, and the complex viscosity of GME printed samples was greater than that of FME counterparts. Remarkably, the average molecular weights of GME printed samples were higher than those of FME ones, which can be attributed to lower actual temperature of the GME extrusion chamber due to its different location among the heater, thermistor and melting chamber compared to the FME extrusion head.ye
Strategies for developing shape-shifting behaviours and potential applications of poly(N-vinyl Caprolactam) hydrogels
Get PDFStimuli-responsive hydrogels are one type of smart hydrogel, which can expand/contract in
water according to changes in the surrounding environment. However, it is difficult to develop flexible
shapeshifting behaviours by using a single hydrogel material. This study exploited a new method to
utilise single and bilayer structures to allow hydrogel-based materials to exhibit controllable shapeshifting
behaviours. Although other studies have demonstrated similar transformation behaviours,
this is the first report of such smart materials developed using photopolymerised N-vinyl caprolactam
(NVCL)-based polymers. Our contribution provides a straightforward method in the fabrication
of deformable structures. In the presence of water, the bending behaviours (vertex-to-vertex and
edge-to-edge) were achieved in monolayer squares. By controlling the content and combination of
the NVCL solutions with elastic resin, the bilayer strips were prepared. The expected reversible
self-bending and self-helixing behaviours were achieved in specific types of samples. In addition,
by limiting the expansion time of the bilayer, the layered flower samples exhibited predictable selfcurving
shape transformation behaviour in at least three cycles of testing. These structures displayed
the capacity of self-transformation, and the value and functionality of the produced components are
reflected in this paper.ye
Steamed hams and bashing tans - analysing Irish political discourse through internet memes in a simpsons facebook group
Get PDFPolitical participation has evolved dramatically in the last 20 years. New media technologies and online spaces have enabled people to participate in politics and express their opinions in ways that were not possible in the past. One of the ways users can express their political opinions is through user generated content known as internet memes. Memes are images, videos, or pieces of text that are often humorous and spread rapidly on the internet and have become a staple in online communication. They can be used to convey a wide range of ideas and influence social attitudes in contemporary society (Shifman, 2014). Previous studies on internet memes have looked at their role in political engagement and activism, as well as their influence on political campaigns such as the 2016 US Presidential Elections (Ross & Rivers, 2018) and Brexit (Kinane, 2021). However, majority of these studies have been conducted in the context of the US or the UK and there is little to no research on the use of memes in Ireland. The purpose of this research is to analyse Irish political discourse through internet memes. This study looks at interactions on Irish politics through memes created by members of the Ireland Simpsons Fans Facebook Group. The research indicates that these spaces have the potential to shape social and political attitude formation in the public sphere due to their accessibility and the level of camaraderie identified in the group dynamics.ye
Synthesis and characterization of silver nanoparticles for the preparation of Chitosan pellets and their application in industrial wastewater disinfection
No full textThe use of silver nanoparticles (AgNPs) has become popular in several applications due to
their bactericidal properties. In this sense, it is ideal that the AgNPs are incorporated into a matrix
in order to minimize their release to the environment and to maintain their high reactivity. In view
of these facts, the main goal of this work was to synthesize and characterize AgNPs, evaluating the
influence of pH on the synthesis, for later incorporation into a chitosan polymeric matrix that will be
used in the form of pellets for the disinfection of industrial wastewater. For this purpose, AgNPs were
initially synthesized by a chemical route using silver nitrate, sodium borohydride and sodium citrate
and then characterized by ultraviolet-visible spectroscopy, transmission electron microscopy and as a
function of bacterial growth inhibition against Escherichia coli and Enterococcus faecalis. At the end
of this procedure, AgNPs were incorporated in chitosan and the pellets formed were employed in the
disinfection process, while assessing their bactericidal activity as well as the amount of silver leached.
In general, the results showed that AgNPs synthesized at pH 10.0 were smaller (3.14 0.54 nm)
and presented greater dispersion than the AgNPs synthesized at other pH values. Furthermore, it
was possible to observe a synergistic effect between chitosan and AgNPs and the chitosan pellets
containing AgNPs proved to be effective in wastewater treatment, destroying Escherichia coli after
60 min of treatment. Finally, by considering the ease of application, the low environmental impact
and the bactericidal action, it is concluded that the hybrid pellets developed in this work have great
potential to be used as auxiliaries in wastewater treatment.ye
Aarhus Academy: Access to environmental justice myth buster.
No full textThis paper is one of a series of papers designed as a resource for NGOs and those working on EU legislative developments. It summarises the most common arguments made against including Aarhus Convention rights in EU laws relating to the environment, and exposes the flaws in the basis of them. This paper is structured in FAQ format and focuses on Access to Justice on the Environment
Development of lab-simulated slow pyrolysis and generation of pyrolysis profiles of common hydrocarbon polymers for fire debris analysis
No full textThis study aimed to investigate the pyrolysis behaviour of substrates and the influence of various factors on the formation of degradation products through experimental and real world simulations. Experimental simulation involved the pyrolysis of substrates in an inert environment constructed of a glass ampoule and steel compartment. Real world simulation involved the pyrolysis of substrates under a thin metal sheet with external heat from a propane torch. Experimental simulation results illustrate the formation of aromatics from common polymers were possible when the temperature exceeded 550 ℃ for 30 min. The presence of a matrix profile can be masked by ignitable liquids when the ratio was greater than the substrate. Samples subjected to 550 ℃ pyrolysis produced strong positive correlation between all samples regardless of the substrate types or presence of ignitable liquid. Samples with similar chemical structure, such as PP, HDPE, LDPE had greater correlation between themselves compared to phenyl ring structured PER and PET. Nylon sample had closer correlation with aliphatic PP, HDPE, and LDPE. Aliphatic samples subjected to ≤300 ℃ pyrolysis had negative correlation with both aromatic (PC1) and oxygenated products (PC2). There was no secondary cracking for the cyclisation process to take place.n
Benchmarking communicative reinforcement learning frameworks on multi-robot cooperative tasks
Get PDFIndustry 4.0 warehousing is characterised by autonomous multi-robot collaboration systems (MRSs) along with other technologies such as digital communication capabilities and the Internet of Things. These MRSs need to behave coherently for the efficient completion of the assigned cooperative tasks. Multi-agent reinforcement learning (MARL) frameworks are currently considered state-of-the-art to control the behaviour of autonomous MRSs. These MARL frameworks can be with learnable or predefined communication. Current works lack any worthwhile evaluation of communicative MARL frameworks on multi-robot cooperative tasks. This work empirically evaluates current state-of-the-art seminal learnable communicative MARL frameworks by comparing their performance against non-communicative MARL frameworks on multi-robot coop-erative tasks in the context of Industry 4.0 warehousing with the assumptions of partial observability and reward sparsity. The results demonstrate that communicative MARL frameworks outperform their counterparts by a fair margin in training (average returns between 11 and 6 against 8 and 4 for highest and lowest values respectively) and execution performances (average returns between 1.24 and 0.29 against 0.49 and 0.19 for highest and lowest values respectively). This leads to the conclusion that communicative MARL is better suited to multi-robot cooperative tasks under the above-mentioned assumptions.ye
Benford's law applied to digital forensic analysis
Get PDFTampered digital multimedia content has been increasingly used in a wide set of cyberattacks, challenging criminal investigations and law enforcement authorities. The motivations are immense and
range from the attempt to manipulate public opinion by disseminating fake news to digital kidnapping
and ransomware, to mention a few cybercrimes that use this medium as a means of propagation.
Digital forensics has recently incorporated a set of computational learning-based tools to automatically
detect manipulations in digital multimedia content. Despite the promising results attained by machine
learning and deep learning methods, these techniques require demanding computational resources and
make digital forensic analysis and investigation expensive. Applied statistics techniques have also been
applied to automatically detect anomalies and manipulations in digital multimedia content by statistically analysing the patterns and features. These techniques are computationally faster and have been
applied isolated or as a member of a classifier committee to boost the overall artefact classification.
This paper describes a statistical model based on Benford's Law and the results obtained with a dataset
of 18000 photos, being 9000 authentic and the remaining manipulated.
Benford's Law dates from the 18th century and has been successfully adopted in digital forensics,
namely in fraud detection. In the present investigation, Benford's law was applied to a set of features
(colours, textures) extracted from digital images. After extracting the first digits, the frequency with
which they occurred in the set of values obtained from that extraction was calculated. This process
allowed focusing the investigation on the behaviour with which the frequency of each digit occurred in
comparison with the frequency expected by Benford's law.
The method proposed in this paper for applying Benford's Law uses Pearson's and Spearman's correlations and Cramer-Von Mises (CVM) fitting model, applied to the first digit of a number consisting of
several digits, obtained by extracting digital photos features through Fast Fourier Transform (FFT) method.
The overall results obtained, although not exceeding those attained by machine learning approaches,
namely Support Vector Machines (SVM) and Convolutional Neural Networks (CNN), are promising, reaching
an average F1-score of 90.47% when using Pearson correlation. With non-parametric approaches, namely
Spearman correlation and CVM fitting model, an F1-Score of 56.55% and 76.61% were obtained respectively. Furthermore, the Pearson's model showed the highest homogeneity compared to the Spearman's
and CVM models in detecting manipulated images, 8526, and authentic ones, 7662, due to the strong
correlation between the frequencies of each digit and the frequency expected by Benford's law.
The results were obtained with different feature sets length, ranging from 3000 features to the totality
of the features available in the digital image. However, the investigation focused on extracting 1000
features since it was concluded that increasing the features did not imply an improvement in the results.
The results obtained with the model based on Benford's Law compete with those obtained from the
models based on CNN and SVM, generating confidence regarding its application as decision support in a
criminal investigation for the identification of manipulated images.ye