Relationships between Urban Form and Travel Behaviour in Athens, Greece. A Comparison with Western European and North American Results

In Athens, a series of political events during the last two centuries influenced urban planning, resulting in a unique land use and transport system. In this paper, we examine their relationships in this uncommon system and compare them with those in Western European and North American cities. Data from Metro Development Study (1996) were employed in multiple regression models for Athens, while results from similar studies in Western cities were used as the basis for comparisons. The results for Athens show that residential density is a key factor influencing mainly modal split, whereas distance from city centre and the extent of road network mainly influence trip length and energy consumption by car. An interesting threshold of 200 persons/ha is identified, in which significant changes in travel behaviour occur. In contrast, “land use mix” appeared to have no effects on travel behaviour. The international comparisons revealed differences regarding the density threshold and the role of land use mix, while results concerning residential density, distance from city centre and socio-economic characteristics are in line with those from other European and American cities. The case of Athens adds to the notion that land use policies could constitute a tool for changing travel behaviour. However, urban form parameters, and their critical thresholds, may vary from country to country, especially among cities in Europe and America, which means that no universal standards can be adopted. Finally, it could be argued that in all cases, if more compact urban structures are adopted, more sustainable travel patterns will emerge

Gene regulatory networks modelling using a dynamic evolutionary hybrid

<p>Abstract</p> <p>Background</p> <p>Inference of gene regulatory networks is a key goal in the quest for understanding fundamental cellular processes and revealing underlying relations among genes. With the availability of gene expression data, computational methods aiming at regulatory networks reconstruction are facing challenges posed by the data's high dimensionality, temporal dynamics or measurement noise. We propose an approach based on a novel multi-layer evolutionary trained neuro-fuzzy recurrent network (ENFRN) that is able to select potential regulators of target genes and describe their regulation type.</p> <p>Results</p> <p>The recurrent, self-organizing structure and evolutionary training of our network yield an optimized pool of regulatory relations, while its fuzzy nature avoids noise-related problems. Furthermore, we are able to assign scores for each regulation, highlighting the confidence in the retrieved relations. The approach was tested by applying it to several benchmark datasets of yeast, managing to acquire biologically validated relations among genes.</p> <p>Conclusions</p> <p>The results demonstrate the effectiveness of the ENFRN in retrieving biologically valid regulatory relations and providing meaningful insights for better understanding the dynamics of gene regulatory networks.</p> <p>The algorithms and methods described in this paper have been implemented in a Matlab toolbox and are available from: <url>http://bioserver-1.bioacademy.gr/DataRepository/Project_ENFRN_GRN/</url>.</p

Combined Deep Learning and Traditional NLP Approaches for Fire Burst Detection Based on Twitter Posts

The current chapter introduces a procedure that aims at determining regions that are on fire, based on Twitter posts, as soon as possible. The proposed scheme utilizes a deep learning approach for analyzing the text of Twitter posts announcing fire bursts. Deep learning is becoming very popular within different text applications involving text generalization, text summarization, and extracting text information. A deep learning network is to be trained so as to distinguish valid Twitter fire-announcing posts from junk posts. Next, the posts labeled as valid by the network have undergone traditional NLP-based information extraction where the initial unstructured text is converted into a structured one, from which potential location and timestamp of the incident for further exploitation are derived. Analytic processing is then implemented in order to output aggregated reports which are used to finally detect potential geographical areas that are probably threatened by fire. So far, the part that has been implemented is the traditional NLP-based and has already derived promising results under real-world conditions’ testing. The deep learning enrichment is to be implemented and expected to build upon the performance of the existing architecture and further improve it

Composite macroH2A/NRF-1 Nucleosomes Suppress Noise and Generate Robustness in Gene Expression

SummaryThe histone variant macroH2A (mH2A) has been implicated in transcriptional repression, but the molecular mechanisms that contribute to global mH2A-dependent genome regulation remain elusive. Using chromatin immunoprecipitation sequencing (ChIP-seq) coupled with transcriptional profiling in mH2A knockdown cells, we demonstrate that singular mH2A nucleosomes occupy transcription start sites of subsets of both expressed and repressed genes, with opposing regulatory consequences. Specifically, mH2A nucleosomes mask repressor binding sites in expressed genes but activator binding sites in repressed genes, thus generating distinct chromatin landscapes that limit genetic or extracellular inductive signals. We show that composite nucleosomes containing mH2A and NRF-1 are stably positioned on gene regulatory regions and can buffer transcriptional noise associated with antiviral responses. In contrast, mH2A nucleosomes without NRF-1 bind promoters weakly and mark genes with noisier gene expression patterns. Thus, the strategic position and stabilization of mH2A nucleosomes in human promoters defines robust gene expression patterns

The dual role of LSD1 and HDAC3 in STAT5-dependent transcription is determined by protein interactions, binding affinities, motifs and genomic positions

STAT5 interacts with other factors to control transcription, and the mechanism of regulation is of interest as constitutive active STAT5 has been reported in malignancies. Here, LSD1 and HDAC3 were identified as novel STAT5a interacting partners in pro-B cells. Characterization of STAT5a, LSD1 and HDAC3 target genes by ChIP-seq and RNA-seq revealed gene subsets regulated by independent or combined action of the factors and LSD1/HDAC3 to play dual role in their activation or repression. Genes bound by STAT5a alone or in combination with weakly associated LSD1 or HDAC3 were enriched for the canonical STAT5a GAS motif, and such binding induced activation or repression. Strong STAT5 binding was see

Pinna nobilis in the Greek seas (NE Mediterranean): on the brink of extinction?

The Mediterranean endemic fan mussel Pinna nobilis is suffering an ongoing basin-scale mass mortality event (MME) since 2016. As most Mediterranean populations have collapsed, the species has been declared as Critically Endangered in the IUCN Red List of threatened species. In an effort to track the progress of the MME and provide updated information on the status of the species in the Greek seas, data collected through dedicated surveys and opportunistic assessments during 2019 and 2020 have been compiled. During surveys conducted at 258 sites, a total of 14,589 fan mussels were recorded, of which 81.1% were dead. Of the remaining 2,762 live individuals, 256 were juveniles. Two marine areas that still sustain living populations were identified, namely Kalloni Gulf (Lesvos Island), and Laganas Bay (Zakynthos Island). The inner part of Kalloni Gulf appears to maintain the largest surviving population of the species in the eastern Mediterranean, with an abundance estimate of 684,000 individuals (95% confidence interval: 322,000-1,453,000). Solitary, potentially resistant, scattered individuals were recorded at several sites. Other previously abundant populations that had been assessed in the past, specifically those of Lake Vouliagmeni (Korinthiakos Gulf), Souda Bay (Crete) and Gera Gulf (Lesvos Island) with a total of ~350,000 individuals, have now been wiped out. Our results document the collapse of most P. nobilis populations throughout the Greek seas. The MME has progressed substantially between early 2019 and mid-2020, as indicated by the increase in mortality at sites consecutively monitored multiple times. This work highlights the urgent need for continuous monitoring of surviving populations and calls for immediate implementation of an effective protection and management strategy that will ensure the persistence of surviving individuals and the production of resistant offspring

Integration of Long-Term-Memory-Related Synaptic Plasticity Involves Bidirectional Regulation of Gene Expression and Chromatin Structure

AbstractExcitatory and inhibitory inputs converge on single neurons and are integrated into a coherent output. Although much is known about short-term integration, little is known about how neurons sum opposing signals for long-term synaptic plasticity and memory storage. In Aplysia, we find that when a sensory neuron simultaneously receives inputs from the facilitatory transmitter 5-HT at one set of synapses and the inhibitory transmitter FMRFamide at another, long-term facilitation is blocked and synapse-specific long-term depression dominates. Chromatin immunoprecipitation assays show that 5-HT induces the downstream gene C/EBP by activating CREB1, which recruits CBP for histone acetylation, whereas FMRFa leads to CREB1 displacement by CREB2 and recruitment of HDAC5 to deacetylate histones. When the two transmitters are applied together, facilitation is blocked because CREB2 and HDAC5 displace CREB1-CBP, thereby deacetylating histones