Driver Simulation-Based Training of Heavy Vehicle Operators: Targeted Task Analysis and Considerations for Training Design

The use of simulation for training operators of heavy vehicles is gaining momentum. However, there still exists a gap in knowledge about the appropriate skills to target, and in particular, with regards to skill areas of a nontechnical nature. By taking a first-principles approach, we first sought to conduct a targeted analysis of the heavy vehicle operator task and, in turn, to assess which of the goal-based tasks identified through the task analysis would be most appropriate for simulation-based training. In general, simulation provides a safe and efficient option for training critical skills that could otherwise be trained on road (e.g., gear shifting). Simulation also provides the opportunity to train critical skills in a structured and formal way that could otherwise not be achieved in a real heavy vehicle, except on an opportunistic or incidental basis (e.g., hazard perception). Nonetheless, the challenge for training system design still remains: what constitutes the appropriate balance between simulator-based and real truckbased practical training, and for which curriculum components and skill sets

Fishes of the Cocos (Keeling) Islands: new records, community composition and biogeographic significance

The Cocos (Keeling) Islands comprise the most isolated oceanic atoll in the tropical Indian Ocean and are situated 1000 km south-west of Indonesia. The remoteness of the islands has shaped the composition of marine communities but also limited scientific research. This study summarises field research on the marine fishes of the Cocos (Keeling) Islands over the last 14 years (2001–2014). Sixty-seven new records (from 28 families) are described and raise the total number of known fishes to 602 species from 84 families. New records span a variety of body sizes (3 cm TL Gobiodon unicolor to 500 cm TL Rhincodon typus), were observed in all major habitats,and found at both the Southern Atoll and at North Keeling Island. Notable new records include first records for the families Alopiidae, Coryphaenidae, Eleotridae, Gempylidae, Istiophoridae, Molidae, Polymixiidae, Rhincodontidae, Sillaginidae and Xiphiidae. Sampling from pelagic and deepwater (60–300 m) reef environments significantly increased the number of species described from these habitats. New records include species that have dispersed more than 2500 km (Centropyge acanthops) and dispersal ability appears to explain the lack of syngnathids and the high representation of acanthurids and holocentrids in the community. Some of the Indian Ocean species that have colonised the Cocos (Keeling) Islands now co-occur with their Pacific Ocean sister species, increasing the potential for hybridisation. Although the fish community of the Cocos (Keeling) Island resembles that of the Indo-West Pacific, the isolation and co-occurrence of Indian and Pacific Ocean species distinguishes it from all other locations

Checklist and new records of Christmas Island fishes: the influence of isolation, biogeography and habitat availability on species abundance and community composition

Christmas Island (Indian Ocean) is an oceanic high island that is situated 300 km southwest of Java, Indonesia. From 2010 to 2014, the fish community of Christmas Island was surveyed using underwater visual surveys for shallow water (0–60 m) fishes, and line fishing (bottom fishing and trolling) for deepwater (60–300 m) and pelagic fishes. Forty-seven new records (from 22 families) were identified, thereby increasing the total number of fishes described from Christmas Island to 681 (from 91 families). Notable new records include the first records for the families Alopiidae, Anomalopidae, Muraenesocidae, Tetrarogidae and Trichonotidae, and the first reports of Pacific Ocean species Plectranthias yamakawai, and Polylepion russelli in the Indian Ocean. The ten most species-rich families accounted for 58% of the community and included: Labridae (13%), Pomacentridae (8%), Epinephelidae (6%), Acanthuridae (5%), Chaetodontidae (5%), Muraenidae (5%), Gobiidae (5%), Blenniidae (4%), Apogonidae (4%) and Scorpaenidae (3%). The majority (89%) of species inhabit shallow coral reefs, with deep reefs (60–300 m) and pelagic waters only accounting for 7% and 2% of fish community. Approximately 76% of thefishes are widespread Indo-Pacific species, 12% are Pacific Ocean species, 5% are circumtropical, 4% are Indian Ocean species and approximately 1% are endemic. Abundance surveys revealed that endemic species, and species at the edge of their geographic range, do not conform to terrestrial-based predictions of low abundance. The structure and composition of the Christmas Island fish community is influenced by three main factors. Firstly, the isolation of the island means that fishes with poor dispersal abilities (e.g., syngnathids) are underrepresented. Secondly, thebiogeographic position of the island results in a unique mixing of Indian and Pacific Ocean species. Thirdly, the lack of lagoonal habitats means that fishes that use these habitats (e.g., ophichthids, lethrinids, epinephelids) are underrepresented or have low abundance

Proposing a Governance model for environmental crises

During August 2021, a wildfire outbreak in Evia, Greece's second largest island, resulted in a major environmental and economic crisis. Apart from biodiversity and habitat loss, the disaster triggered a financial crisis because it wiped out wood-productive forests and outdoor areas that attract visitors. This crisis highlighted the need for a new governance model in order to respond to environmental crises more effectively. The aim of this study was to investigate the acceptance and attitudes of relevant stakeholders towards establishing a Hub a proposed governance model responsible for monitoring and restoring the natural capital and biodiversity after environmental crises. Results based on quantitative data collected via questionnaires showed that most respondents were positive to the Hub and perceived that its main functions should be to recommend measures after environmental crises and to facilitate cooperation among involved stakeholders. Moreover, results pointed to preferred funding sources, stakeholder groups that should participate in the Hub and key performance indicators (KPIs) for monitoring Hub's performance. The applied methodology could guide the establishment of governance models both in the study area and other countries facing environmental crises

Deriving a mutation index of carcinogenicity using protein structure and protein interfaces

With the advent of Next Generation Sequencing the identification of mutations in the genomes of healthy and diseased tissues has become commonplace. While much progress has been made to elucidate the aetiology of disease processes in cancer, the contributions to disease that many individual mutations make remain to be characterised and their downstream consequences on cancer phenotypes remain to be understood. Missense mutations commonly occur in cancers and their consequences remain challenging to predict. However, this knowledge is becoming more vital, for both assessing disease progression and for stratifying drug treatment regimes. Coupled with structural data, comprehensive genomic databases of mutations such as the 1000 Genomes project and COSMIC give an opportunity to investigate general principles of how cancer mutations disrupt proteins and their interactions at the molecular and network level. We describe a comprehensive comparison of cancer and neutral missense mutations; by combining features derived from structural and interface properties we have developed a carcinogenicity predictor, InCa (Index of Carcinogenicity). Upon comparison with other methods, we observe that InCa can predict mutations that might not be detected by other methods. We also discuss general limitations shared by all predictors that attempt to predict driver mutations and discuss how this could impact high-throughput predictions. A web interface to a server implementation is publicly available at http://inca.icr.ac.uk/

Sequencing of prostate cancers identifies new cancer genes, routes of progression and drug targets

Prostate cancer represents a substantial clinical challenge because it is difficult to predict outcome and advanced disease is often fatal. We sequenced the whole genomes of 112 primary and metastatic prostate cancer samples. From joint analysis of these cancers with those from previous studies (930 cancers in total), we found evidence for 22 previously unidentified putative driver genes harboring coding mutations, as well as evidence for NEAT1 and FOXA1 acting as drivers through noncoding mutations. Through the temporal dissection of aberrations, we identified driver mutations specifically associated with steps in the progression of prostate cancer, establishing, for example, loss of CHD1 and BRCA2 as early events in cancer development of ETS fusion-negative cancers. Computational chemogenomic (canSAR) analysis of prostate cancer mutations identified 11 targets of approved drugs, 7 targets of investigational drugs, and 62 targets of compounds that may be active and should be considered candidates for future clinical trials

Comprehensive Genomic Analysis of a BRCA2 Deficient Human Pancreatic Cancer

Capan-1 is a well-characterised BRCA2-deficient human cell line isolated from a liver metastasis of a pancreatic adenocarcinoma. Here we report a genome-wide assessment of structural variations and high-depth exome characterization of single nucleotide variants and small insertion/deletions in Capan-1. To identify potential somatic and tumour-associated variations in the absence of a matched-normal cell line, we devised a novel method based on the analysis of HapMap samples. We demonstrate that Capan-1 has one of the most rearranged genomes sequenced to date. Furthermore, small insertions and deletions are detected more frequently in the context of short sequence repeats than in other genomes. We also identify a number of novel mutations that may represent genetic changes that have contributed to tumour progression. These data provide insight into the genomic effects of loss of BRCA2 function

Plasticity in dendroclimatic response across the distribution range of Aleppo pine (Pinus halepensis)

We investigated the variability of the climate-growth relationship of Aleppo pine across its distribution range in the Mediterranean Basin. We constructed a network of tree-ring index chronologies from 63 sites across the region. Correlation function analysis identified the relationships of tree-ring index to climate factors for each site. We also estimated the dominant climatic gradients of the region using principal component analysis of monthly, seasonal, and annual mean temperature and total precipitation from 1,068 climatic gridpoints. Variation in ring width index was primarily related to precipitation and secondarily to temperature. However, we found that the dendroclimatic relationship depended on the position of the site along the climatic gradient. In the southern part of the distribution range, where temperature was generally higher and precipitation lower than the regional average, reduced growth was also associated with warm and dry conditions. In the northern part, where the average temperature was lower and the precipitation more abundant than the regional average, reduced growth was associated with cool conditions. Thus, our study highlights the substantial plasticity of Aleppo pine in response to different climatic conditions. These results do not resolve the source of response variability as being due to either genetic variation in provenance, to phenotypic plasticity, or a combination of factors. However, as current growth responses to inter-annual climate variability vary spatially across existing climate gradients, future climate-growth relationships will also likely be determined by differential adaptation and/or acclimation responses to spatial climatic variation. The contribution of local adaptation and/or phenotypic plasticity across populations to the persistence of species under global warming could be decisive for prediction of climate change impacts across populations. In this sense, a more complex forest dynamics modeling approach that includes the contribution of genetic variation and phenotypic plasticity can improve the reliability of the ecological inferences derived from the climate-growth relationships.This work was partially supported by Spanish Ministry of Education and Science co-funded by FEDER program (CGL2012-31668), the European Union and the National Ministry of Education and Religion of Greece (EPEAEK- Environment – Archimedes), the Slovenian Research Agency (program P4-0015), and the USDA Forest Service. The cooperation among international partners was supported by the COST Action FP1106, STREeSS

Screening out irrelevant cell-based models of disease

The common and persistent failures to translate promising preclinical drug candidates into clinical success highlight the limited effectiveness of disease models currently used in drug discovery. An apparent reluctance to explore and adopt alternative cell-and tissue-based model systems, coupled with a detachment from clinical practice during assay validation, contributes to ineffective translational research. To help address these issues and stimulate debate, here we propose a set of principles to facilitate the definition and development of disease-relevant assays, and we discuss new opportunities for exploiting the latest advances in cell-based assay technologies in drug discovery, including induced pluripotent stem cells, three-dimensional (3D) co-culture and organ-on-a-chip systems, complemented by advances in single-cell imaging and gene editing technologies. Funding to support precompetitive, multidisciplinary collaborations to develop novel preclinical models and cell-based screening technologies could have a key role in improving their clinical relevance, and ultimately increase clinical success rates