Mercury and Water Quality Study. Impact of Gold Mining in Song Bung 4 Project Area, Central Vietnam

Årsliste 2006The aim of this study is to elucidate any impact that the mining activity in the catchment of Song Bung River has on the water quality, sediment quality, as well as for the fish and the fish flesh quality in the mainstream river and in some tributaries in the Song Bung 4 hydropower development project area. In Song Bung mainstream enhanced concentrations of mercury were found both in the water and in the sediments in the river stretch where gold dredging activity was carried out. The concentrations were however low, much lower than problem levels both in national and internationally recognized environmental quality guidelines. This also applied for the tributaries. For arsenic and all other heavy metals normally confined with mining activity, observed concentrations were all lower than levels known to give environmental or consumption concerns. In the downstream part of the tributaries no traces of cyanide pollution were detected. The concentrations of mercury and other heavy metals in fish flesh were all low, and well below the WHO standards for consumption. The sediment dredging had only moderate impact on river water turbidity. However, the dredging made large physical disturbances of river habitats in the dredged sections of the rivers. Otherwise the water quality of Song Bung River was good and was to a low degree impacted by human activities. The mercury pollution of river sediments from the gold mining was so small that it will not create problems in the planned reservoir of Song Bung 4 Hydropower plant.Asian Development Ban

Quantifying the Emergence of Dengue in Hanoi, Vietnam: 1998–2009

Dengue is the most common vector-borne viral disease of humans, causing an estimated 50 million cases per year. The number of countries affected by dengue has increased dramatically in the last 50 years and dengue is now a major public health problem in large parts of the tropical and subtropical world. It is of considerable importance to understand the factors that determine how dengue becomes newly established in areas where the risk of dengue was previously small. Hanoi in North Vietnam is a large city where dengue appears to be emerging. We analyzed 12 years of dengue surveillance data in order to characterize the temporal and spatial epidemiology of dengue in Hanoi and to establish if dengue incidence has been increasing. After excluding the two major outbreak years of 1998 and 2009 and correcting for changes in population age structure over time, we found there was a significant annual increase in the incidence of notified dengue cases over the period 1999–2008. Dengue cases were concentrated in young adults in the highly urban central areas of Hanoi. This study indicates that dengue transmission is increasing in Hanoi and provides a platform for further studies of the underlying drivers of this emergence

Dengue Dynamics in Binh Thuan Province, Southern Vietnam: Periodicity, Synchronicity and Climate Variability

Dengue has become a major international public health problem due to increasing geographic distribution and a transition from epidemic transmission with long inter-epidemic intervals to endemic transmission with seasonal fluctuation. Seasonal and multi-annual cycles in dengue incidence vary over time and space. We performed wavelet analyses on time series of monthly notified dengue cases in Binh Thuan province, southern Vietnam, from January 1994 to June 2009. We observed a continuous annual mode of oscillation with a non-stationary 2–3-year multi-annual cycle. We used phase differences to describe the spatio-temporal patterns which suggest that the seasonal wave of infection was either synchronous with all districts or moving away from Phan Thiet district, while the multi-annual wave of infection was moving towards Phan Thiet district. We also found a strong non-stationary association between ENSO indices and climate variables with dengue incidence. We provided insight in dengue population transmission dynamics over the past 14.5 years. Further studies on an extensive time series dataset are needed to test the hypothesis that epidemics emanate from larger cities in southern Vietnam

What is the future for nuclear fission technology? A technical opinion from the Guest Editors of VSI NFT series and the Editor of the Journal Nuclear Engineering and Design

The Nuclear Fission Technology (NFT) series of Virtual Special Issues (VSIs) for the Journal Nuclear Engineering and Design (J NED) was proposed in 2023, including the request to potential authors of manuscript to address the following questions: o For how long will (water-cooling based) large size nuclear reactor survive? o Will water-technology based SMRs displace large reactors? o Will non-water-cooling technology SMRs and micro-reactors have an industrial deployment? o Will breeding technology, including thorium exploitation, have due relevance? o Will ‘nuclear infrastructure’ (fuel supply, financial framework, competence by regulators for new designs, waste management, etc.) remain or be sufficiently robust? Several dozen Guest Editors (GEs), i.e., the authors of the present document, managed the activity together with the Editor-in-Chief (EiC) of the journal. More than one thousand scientists contributed 470+ manuscripts, not evenly distributed among the geographical regions of the world and not necessarily addressing directly the bullet-questions, but certainly providing a view of current research being done. Key conclusions are as follows: (a) Large size reactors are necessary for a sustainable and safe exploitation of nuclear fission technology; (b) The burning of 233U (from thorium) and 239Pu (from uranium) is unavoidable, as well as recycling residual uranium currently part of waste; (c) Nuclear infrastructures in countries that currently use, or are entering the use of, fission energy for electricity production need a century planning; (d) The adoption of small reactors for commercial naval propulsion, hydrogen production and desalination is highly recommended

The genetic architecture of the human cerebral cortex

The cerebral cortex underlies our complex cognitive capabilities, yet little is known about the specific genetic loci that influence human cortical structure. To identify genetic variants that affect cortical structure, we conducted a genome-wide association meta-analysis of brain magnetic resonance imaging data from 51,665 individuals. We analyzed the surface area and average thickness of the whole cortex and 34 regions with known functional specializations. We identified 199 significant loci and found significant enrichment for loci influencing total surface area within regulatory elements that are active during prenatal cortical development, supporting the radial unit hypothesis. Loci that affect regional surface area cluster near genes in Wnt signaling pathways, which influence progenitor expansion and areal identity. Variation in cortical structure is genetically correlated with cognitive function, Parkinson's disease, insomnia, depression, neuroticism, and attention deficit hyperactivity disorder

The Immune Landscape of Cancer

We performed an extensive immunogenomic anal-ysis of more than 10,000 tumors comprising 33diverse cancer types by utilizing data compiled byTCGA. Across cancer types, we identified six im-mune subtypes\u2014wound healing, IFN-gdominant,inflammatory, lymphocyte depleted, immunologi-cally quiet, and TGF-bdominant\u2014characterized bydifferences in macrophage or lymphocyte signa-tures, Th1:Th2 cell ratio, extent of intratumoral het-erogeneity, aneuploidy, extent of neoantigen load,overall cell proliferation, expression of immunomod-ulatory genes, and prognosis. Specific drivermutations correlated with lower (CTNNB1,NRAS,orIDH1) or higher (BRAF,TP53,orCASP8) leukocytelevels across all cancers. Multiple control modalitiesof the intracellular and extracellular networks (tran-scription, microRNAs, copy number, and epigeneticprocesses) were involved in tumor-immune cell inter-actions, both across and within immune subtypes.Our immunogenomics pipeline to characterize theseheterogeneous tumors and the resulting data areintended to serve as a resource for future targetedstudies to further advance the field

Dynamic social community detection and its applications.

Community structure is one of the most commonly observed features of Online Social Networks (OSNs) in reality. The knowledge of this feature is of great advantage: it not only provides helpful insights into developing more efficient social-aware solutions but also promises a wide range of applications enabled by social and mobile networking, such as routing strategies in Mobile Ad Hoc Networks (MANETs) and worm containment in OSNs. Unfortunately, understanding this structure is very challenging, especially in dynamic social networks where social interactions are evolving rapidly. Our work focuses on the following questions: How can we efficiently identify communities in dynamic social networks? How can we adaptively update the network community structure based on its history instead of recomputing from scratch? To this end, we present Quick Community Adaptation (QCA), an adaptive modularity-based framework for not only discovering but also tracing the evolution of network communities in dynamic OSNs. QCA is very fast and efficient in the sense that it adaptively updates and discovers the new community structure based on its history together with the network changes only. This flexible approach makes QCA an ideal framework applicable for analyzing large-scale dynamic social networks due to its lightweight computing-resource requirement. To illustrate the effectiveness of our framework, we extensively test QCA on both synthesized and real-world social networks including Enron, arXiv e-print citation, and Facebook networks. Finally, we demonstrate the applicability of QCA in real applications: (1) A social-aware message forwarding strategy in MANETs, and (2) worm propagation containment in OSNs. Competitive results in comparison with other methods reveal that social-based techniques employing QCA as a community detection core outperform current available methods